Triple
T31656315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New New York City |
E807865
|
entity |
| Predicate | hasFictionalSportsVenue |
P116761
|
FINISHED |
| Object | Madison Cube Garden |
—
|
NE NERFINISHED |
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: Madison Cube Garden | Statement: [New New York City, hasFictionalSportsVenue, Madison Cube Garden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalSportsVenue Context triple: [New New York City, hasFictionalSportsVenue, Madison Cube Garden]
-
A.
hasProfessionalSportsVenue
Indicates that one entity possesses or hosts a venue specifically used for professional sports events.
-
B.
isProfessionalSportsVenue
Indicates that a venue is primarily used for hosting professional-level sporting events or competitions.
-
C.
hasFictionalLandmark
chosen
Indicates that one entity includes, features, or is associated with a landmark that is fictional rather than real.
-
D.
hasSportsTeamVenueFor
Indicates that a venue serves as the home or hosting location for a particular sports team.
-
E.
hasAssociatedSportsVenue
Indicates that an entity is linked to a specific sports venue with which it is functionally or contextually associated.
- 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_69f348daf95c81908b4c985b7ddcd0b3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe920a437081908d5174e8cf7a53a6 |
completed | May 9, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69fe919a9a6c8190acb4483f386e6db7 |
completed | May 9, 2026, 1:44 a.m. |
Created at: April 30, 2026, 10:55 p.m.