Triple
T1466020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carolina Hurricanes |
E27022
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
CAR
CAR is the standard NHL abbreviation for the Carolina Hurricanes professional ice hockey team.
|
E167171
|
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: CAR | Statement: [Carolina Hurricanes, abbreviation, CAR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CAR Context triple: [Carolina Hurricanes, abbreviation, CAR]
-
A.
CAR
CAR is a research center dedicated to advancing the understanding, diagnosis, and treatment of autism spectrum disorders through scientific study and clinical collaboration.
-
B.
Cars
Cars is a 2006 Pixar animated film that follows a hotshot race car who discovers friendship and humility in a forgotten desert town.
-
C.
Mobil
Mobil is a major American oil company and fuel brand that became part of ExxonMobil after a 1999 merger.
-
D.
Cars.TV
Cars.TV is a television network and media outlet focused on automotive-related programming, including car reviews, industry news, and enthusiast content.
-
E.
Motor Mania
Motor Mania is a 1950 Disney animated short film featuring Goofy that humorously depicts the transformation of a mild-mannered driver into an aggressive road menace.
- 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: CAR Triple: [Carolina Hurricanes, abbreviation, CAR]
Generated description
CAR is the standard NHL abbreviation for the Carolina Hurricanes professional ice hockey team.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CAR Target entity description: CAR is the standard NHL abbreviation for the Carolina Hurricanes professional ice hockey team.
-
A.
CAR
CAR is a research center dedicated to advancing the understanding, diagnosis, and treatment of autism spectrum disorders through scientific study and clinical collaboration.
-
B.
Cars
Cars is a 2006 Pixar animated film that follows a hotshot race car who discovers friendship and humility in a forgotten desert town.
-
C.
Mobil
Mobil is a major American oil company and fuel brand that became part of ExxonMobil after a 1999 merger.
-
D.
Cars.TV
Cars.TV is a television network and media outlet focused on automotive-related programming, including car reviews, industry news, and enthusiast content.
-
E.
Motor Mania
Motor Mania is a 1950 Disney animated short film featuring Goofy that humorously depicts the transformation of a mild-mannered driver into an aggressive road menace.
- 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_69a496d25d6881909dbd84f86d763992 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c5bb4e288190997c7e8985e9a2bd |
completed | March 1, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad0e7e7f848190a8abcb73e89e8e34 |
completed | March 8, 2026, 5:51 a.m. |
| NEDg | Description generation | batch_69ad0f0b145c8190b08af9a6a3325c23 |
completed | March 8, 2026, 5:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad0f90cdec81908a981e12184cdd75 |
completed | March 8, 2026, 5:56 a.m. |
Created at: March 1, 2026, 8:01 p.m.