Triple
T31125156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Animals |
E793334
|
entity |
| Predicate | photographsTakenAt |
P139859
|
FINISHED |
| Object | Bronx Zoo |
—
|
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: Bronx Zoo | Statement: [The Animals, photographsTakenAt, Bronx Zoo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: photographsTakenAt Context triple: [The Animals, photographsTakenAt, Bronx Zoo]
-
A.
photographsTakenIn
Indicates that photographs were captured or taken within a specific location or place.
-
B.
oftenPhotographedAt
Indicates that an entity is frequently the subject of photographs taken at a particular location or during a specific event.
-
C.
photographTakenAt
chosen
Indicates that a photograph was captured at a specific location or during a particular event or time.
-
D.
photographedFrom
Indicates that one entity serves as the vantage point or location from which another entity is photographed.
-
E.
capturedPlace
Indicates that an agent took control of or seized a specific place, typically through force or strategic action.
- 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_69f224d1701c819094f429798290e361 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69c234d648190a243fb2b107136a9 |
completed | May 3, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69f69665cd9c819088c388fc82fec42e |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 9:05 p.m.