Triple
T2610891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1000 Fifth Avenue, New York, NY |
E58768
|
entity |
| Predicate | hasVisitorEntrance |
P6140
|
FINISHED |
| Object | Metropolitan Museum of Art main entrance |
—
|
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: Metropolitan Museum of Art main entrance | Statement: [1000 Fifth Avenue, New York, NY, hasVisitorEntrance, Metropolitan Museum of Art main entrance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVisitorEntrance Context triple: [1000 Fifth Avenue, New York, NY, hasVisitorEntrance, Metropolitan Museum of Art main entrance]
-
A.
hasEntrance
chosen
Indicates that one entity possesses or provides an entry point or access way to another entity or space.
-
B.
hasEntranceStructure
Indicates that one entity possesses or is associated with a specific physical structure that serves as its entrance.
-
C.
hasEntranceOn
Indicates that one entity’s entrance or access point is located on or faces a specified side, boundary, or feature of another entity.
-
D.
hasNumberOfEntrances
Indicates the relationship that specifies how many entrances an entity possesses.
-
E.
hasSeparateEntrances
Indicates that the related entities each have their own distinct entrance, rather than sharing a common one.
- 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_69ab4ac3523881909679750c9f8c2dec |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd89325308190985598373eb0d296 |
completed | March 7, 2026, 7:49 a.m. |
| PD | Predicate disambiguation | batch_69abd80cd7fc81909e9696db2919129f |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.