Triple
T15594991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One to One |
E374868
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Lookin’ Out for Number One
"Lookin’ Out for Number One" is a song by the Canadian rock band One to One.
|
E1166722
|
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: Lookin’ Out for Number One | Statement: [One to One, hasPart, Lookin’ Out for Number One]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lookin’ Out for Number One Context triple: [One to One, hasPart, Lookin’ Out for Number One]
-
A.
To Be Number One
To Be Number One is the English-language version of the official song of the 1990 FIFA World Cup, originally released in Italian as "Un'estate italiana" and widely associated with that tournament.
-
B.
Number One
Number One is the composed and highly capable first officer of the USS Enterprise in the Star Trek universe, originally introduced in the 1960s pilot and later portrayed by Rebecca Romijn in modern series.
-
C.
Number One
"Number One" is a song by John Legend from his debut studio album "Get Lifted."
-
D.
Number One
Number One is the Balmoral Hotel’s acclaimed fine-dining restaurant in Edinburgh, known for its refined Scottish cuisine and elegant setting.
-
E.
Number One
"Number One" is a hit Bongo Flava song by Tanzanian artist Diamond Platnumz that significantly boosted his popularity across East Africa.
- 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: Lookin’ Out for Number One Triple: [One to One, hasPart, Lookin’ Out for Number One]
Generated description
"Lookin’ Out for Number One" is a song by the Canadian rock band One to One.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lookin’ Out for Number One Target entity description: "Lookin’ Out for Number One" is a song by the Canadian rock band One to One.
-
A.
To Be Number One
To Be Number One is the English-language version of the official song of the 1990 FIFA World Cup, originally released in Italian as "Un'estate italiana" and widely associated with that tournament.
-
B.
Number One
Number One is the composed and highly capable first officer of the USS Enterprise in the Star Trek universe, originally introduced in the 1960s pilot and later portrayed by Rebecca Romijn in modern series.
-
C.
Number One
"Number One" is a song by John Legend from his debut studio album "Get Lifted."
-
D.
Number One
Number One is the Balmoral Hotel’s acclaimed fine-dining restaurant in Edinburgh, known for its refined Scottish cuisine and elegant setting.
-
E.
Number One
"Number One" is a hit Bongo Flava song by Tanzanian artist Diamond Platnumz that significantly boosted his popularity across East Africa.
- 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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e5f9db8819083abf80f01f32b3d |
completed | April 16, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56c7db58819089cb488fb3ea96cd |
completed | May 9, 2026, 3:46 p.m. |
| NEDg | Description generation | batch_69ff58687e4c8190a4054c4d5419a76a |
completed | May 9, 2026, 3:53 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff58d92218819085877be120fdcc01 |
completed | May 9, 2026, 3:55 p.m. |
Created at: April 10, 2026, 4:12 a.m.