Triple
T15165470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Perfume |
E362327
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Laser Beam
"Laser Beam" is a song by the Japanese electropop group Perfume, known for its catchy techno-pop sound and futuristic production.
|
E1141536
|
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: Laser Beam | Statement: [Perfume, notableWork, Laser Beam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laser Beam Context triple: [Perfume, notableWork, Laser Beam]
-
A.
Laser
Laser is the costumed mascot representing Lasell University at its athletic events and campus activities.
-
B.
Laser
Laser is a teenage son in the 2010 film "The Kids Are All Right," whose curiosity about his biological father helps drive the story’s family-centered plot.
-
C.
Wonskolaser
Wonskolaser is the original family surname of Harry Warner, one of the co-founding Warner brothers of Warner Bros. Studios.
-
D.
Lazers
Lazers is the abbreviated name of the Los Angeles Lazers, a former professional indoor soccer team that competed in the Major Indoor Soccer League during the 1980s.
-
E.
Lasers
Lasers is Lupe Fiasco’s third studio album, known for its politically charged lyrics, pop-oriented production, and contentious relationship with both his label and core fanbase.
- 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: Laser Beam Triple: [Perfume, notableWork, Laser Beam]
Generated description
"Laser Beam" is a song by the Japanese electropop group Perfume, known for its catchy techno-pop sound and futuristic production.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laser Beam Target entity description: "Laser Beam" is a song by the Japanese electropop group Perfume, known for its catchy techno-pop sound and futuristic production.
-
A.
Laser
Laser is the costumed mascot representing Lasell University at its athletic events and campus activities.
-
B.
Laser
Laser is a teenage son in the 2010 film "The Kids Are All Right," whose curiosity about his biological father helps drive the story’s family-centered plot.
-
C.
Wonskolaser
Wonskolaser is the original family surname of Harry Warner, one of the co-founding Warner brothers of Warner Bros. Studios.
-
D.
Lazers
Lazers is the abbreviated name of the Los Angeles Lazers, a former professional indoor soccer team that competed in the Major Indoor Soccer League during the 1980s.
-
E.
Lasers
Lasers is Lupe Fiasco’s third studio album, known for its politically charged lyrics, pop-oriented production, and contentious relationship with both his label and core fanbase.
- 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_69d85a087b7c81908baa94a53dac8d68 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0064c6244819085daf8e1eafdf3f2 |
completed | April 15, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fec887fbf08190b42dd25a99b7770d |
completed | May 9, 2026, 5:39 a.m. |
| NEDg | Description generation | batch_69fec974f39c819081dcec5c18090cf7 |
completed | May 9, 2026, 5:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feca9d1a5c8190b0c649f83a74231b |
completed | May 9, 2026, 5:48 a.m. |
Created at: April 10, 2026, 3:08 a.m.