Triple
T3632852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Antolini |
E76996
|
entity |
| Predicate | sceneLocation |
P47308
|
FINISHED |
| Object | his New York City apartment |
—
|
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: his New York City apartment | Statement: [Mr. Antolini, sceneLocation, his New York City apartment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sceneLocation Context triple: [Mr. Antolini, sceneLocation, his New York City apartment]
-
A.
gameLocation
Indicates the place or venue where a game or match takes place.
-
B.
subjectLocation
chosen
Indicates that one entity is located at, in, or near the place or position specified by another entity.
-
C.
locationOfVision
Indicates the place or setting where a vision or visual experience occurs or is perceived.
-
D.
coordinateLocation
Indicates that an entity is located at, or associated with, a specific geographic coordinate or set of coordinates.
-
E.
mapLocation
Indicates a relationship where an entity is associated with a specific position or area on a map.
- 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_69ad85dd0be48190b738990cb20c4731 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc30457608190840fb5b33f9965c4 |
completed | March 8, 2026, 6:42 p.m. |
| PD | Predicate disambiguation | batch_69adb842be7c8190b7dfdb7c906f294c |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:23 p.m.