Triple
T17186085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Things We Lost in the Fire |
E417111
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object |
In Metal
"In Metal" is a song by the American indie rock band Low, featured on their acclaimed 2001 album *Things We Lost in the Fire*.
|
E1256388
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: In Metal | Statement: [Things We Lost in the Fire, hasTrack, In Metal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: In Metal Context triple: [Things We Lost in the Fire, hasTrack, In Metal]
-
A.
Metallo
Metallo is a DC Comics supervillain and cyborg enemy of Superman, typically powered by a kryptonite heart.
-
B.
Metal 2
Metal 2 is Apple’s second-generation low-level graphics and compute API framework designed to deliver improved performance and advanced GPU features on macOS, iOS, and other Apple platforms.
-
C.
Metallostroy
Metallostroy is an urban-type settlement in the Pushkinsky District of Saint Petersburg, Russia, known primarily as a residential and industrial suburb.
-
D.
Metro
Metro is the primary public transportation agency serving Los Angeles County, operating buses, light rail, subway, and other transit services across the region.
-
E.
Metro
Metro is a multinational wholesale and food retail company headquartered in Germany, operating cash-and-carry stores and serving professional customers worldwide.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: In Metal Triple: [Things We Lost in the Fire, hasTrack, In Metal]
Generated description
"In Metal" is a song by the American indie rock band Low, featured on their acclaimed 2001 album *Things We Lost in the Fire*.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: In Metal Target entity description: "In Metal" is a song by the American indie rock band Low, featured on their acclaimed 2001 album *Things We Lost in the Fire*.
-
A.
Metallo
Metallo is a DC Comics supervillain and cyborg enemy of Superman, typically powered by a kryptonite heart.
-
B.
Metal 2
Metal 2 is Apple’s second-generation low-level graphics and compute API framework designed to deliver improved performance and advanced GPU features on macOS, iOS, and other Apple platforms.
-
C.
Metallostroy
Metallostroy is an urban-type settlement in the Pushkinsky District of Saint Petersburg, Russia, known primarily as a residential and industrial suburb.
-
D.
Metro
Metro is the primary public transportation agency serving Los Angeles County, operating buses, light rail, subway, and other transit services across the region.
-
E.
Metro
Metro is a multinational wholesale and food retail company headquartered in Germany, operating cash-and-carry stores and serving professional customers worldwide.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42d962b988190bdbba81ac63c7e6e |
completed | April 19, 2026, 1:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a015fcc424081908a7e74df0523443e |
completed | May 11, 2026, 4:49 a.m. |
| NEDg | Description generation | batch_6a016184e0c0819099320b32bc471cad |
completed | May 11, 2026, 4:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0162692420819097b99a71ec470861 |
completed | May 11, 2026, 5 a.m. |
Created at: April 10, 2026, 5:37 a.m.