Triple
T24474226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Esteban De Jesús |
E617184
|
entity |
| Predicate | notableFightLocation |
P70420
|
FINISHED |
| Object | New York City |
—
|
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: New York City | Statement: [Esteban De Jesús, notableFightLocation, New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableFightLocation Context triple: [Esteban De Jesús, notableFightLocation, New York City]
-
A.
fightsAtLocation
chosen
Indicates that a fighting interaction between entities occurs at a specified location.
-
B.
notableGameLocation
Indicates that a particular place is recognized as a significant or prominent location within a game.
-
C.
notableMatchVenueFor
Indicates that a venue is notably associated with hosting a particular match or game.
-
D.
notableAttackLocation
Indicates the specific place where a significant or notable attack occurred in relation to the subject.
-
E.
significantVenueFor
Indicates that a venue plays an important or notable role in relation to a particular entity, event, or activity.
- 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_69e2d7f197588190889a03e620558059 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f299457ce081909e8d95fd482928dc |
completed | April 29, 2026, 11:50 p.m. |
| PD | Predicate disambiguation | batch_69f287d76c7c81909494f12e606a9149 |
completed | April 29, 2026, 10:36 p.m. |
Created at: April 18, 2026, 2:20 a.m.