Triple
T22917365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teila Tuli |
E568768
|
entity |
| Predicate | martialArtsRecordHighlight |
P150237
|
FINISHED |
| Object | Fought Gerard Gordeau at UFC 1 |
—
|
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: Fought Gerard Gordeau at UFC 1 | Statement: [Teila Tuli, martialArtsRecordHighlight, Fought Gerard Gordeau at UFC 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: martialArtsRecordHighlight Context triple: [Teila Tuli, martialArtsRecordHighlight, Fought Gerard Gordeau at UFC 1]
-
A.
martialArt
Indicates that one entity practices, performs, or is associated with a specific martial art style or discipline in relation to another entity.
-
B.
hasBlackBeltIn
Indicates that an entity holds a black belt rank or equivalent high-level certification in a specified martial art or discipline.
-
C.
boxingRecordSummary
Indicates the summarized outcome or performance record of an entity in boxing matches, such as total wins, losses, and related statistics.
-
D.
combatRecord
Indicates that an entity maintains a documented history of its participation in combat or battles.
-
E.
professionalRecordKOs
Indicates the number of times an entity has won by knockout (KOs) in its professional record.
- F. None of above. chosen
Provenance (4 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_69e2458d90c88190a58cead4e781ca6a |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1807a14648190b5d5f7d926f19320 |
completed | April 29, 2026, 3:52 a.m. |
| PD | Predicate disambiguation | batch_69ef3b7c5fc081909ac50c5c8569cc19 |
completed | April 27, 2026, 10:33 a.m. |
| PDg | Predicate description generation | batch_69ef538a115081908982597f79355840 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 17, 2026, 3:42 p.m.