Triple
T25701105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baby (1983 Broadway musical) |
E644463
|
entity |
| Predicate | numberOfCentralCouples |
P188763
|
FINISHED |
| Object | 3 |
—
|
LITERAL FINISHED |
How this triple was built (2 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: 3 | Statement: [Baby (1983 Broadway musical), numberOfCentralCouples, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCentralCouples Context triple: [Baby (1983 Broadway musical), numberOfCentralCouples, 3]
-
A.
numberOfPairsUsed
Indicates the quantity of distinct pairs involved or utilized in a given context or operation.
-
B.
numberOfCentralStars
Indicates the quantity of central stars associated with or contained within a given entity or system.
-
C.
couplesTo
Indicates that one entity is joined or linked to another in a way that allows interaction, transfer, or mutual influence between them.
-
D.
numberOfMarriages
Indicates the total count of times an entity has been legally married.
-
E.
hasNumberOfCentres
Indicates the relationship specifying how many centers (or central units/locations) are associated with a given entity.
- F. None of above. chosen
Provenance (4 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_69e77e82c9bc8190893090b2f6c64f1d |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fbad1e94988190b86d447a68e65067 |
completed | May 6, 2026, 9:05 p.m. |
| PD | Predicate disambiguation | batch_69fba881b8e0819094790935152b99a1 |
completed | May 6, 2026, 8:45 p.m. |
| PDg | Predicate description generation | batch_69fbad1b3ba08190ad69e21461333f2e |
completed | May 6, 2026, 9:05 p.m. |
Created at: April 21, 2026, 8:45 p.m.