Triple
T23796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Times Square |
E471
|
entity |
| Predicate | isMajorCenterFor |
P164
|
FINISHED |
| Object | entertainment |
—
|
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: entertainment | Statement: [Times Square, isMajorCenterFor, entertainment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMajorCenterFor Context triple: [Times Square, isMajorCenterFor, entertainment]
-
A.
isMajorCenterOf
chosen
Indicates that a place serves as a primary hub or focal point for a particular activity, function, or domain.
-
B.
hasMajorCity
Indicates that a location possesses at least one city of significant size, importance, or influence within its region or country.
-
C.
hasMajorEconomicRegion
Indicates that an entity includes, is associated with, or is part of a primary or significant economic region within a larger economic or geographic context.
-
D.
isEducationalCenterOf
Indicates that an institution functions as the primary educational center serving, representing, or associated with a particular area, organization, or group.
-
E.
hasMajorAirport
Indicates that a location possesses at least one significant airport that serves as a primary hub for air travel in that area.
- F. None of above.
Provenance (3 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246e94ca881908f7a7d2c0b293033 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246560af88190961ea00b35cf9388 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.