Triple
T13469424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chuck Liddell |
E311588
|
entity |
| Predicate | professionalMMARecordNoContests |
P41310
|
FINISHED |
| Object | 0 |
—
|
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: 0 | Statement: [Chuck Liddell, professionalMMARecordNoContests, 0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalMMARecordNoContests Context triple: [Chuck Liddell, professionalMMARecordNoContests, 0]
-
A.
professionalRecordNoContests
chosen
Indicates that an entity’s professional record shows no contests (e.g., bouts or matches that ended without an official result) among its outcomes.
-
B.
professionalMMAStartYear
Indicates the calendar year in which an individual began competing in professional mixed martial arts.
-
C.
numberOfProfessionalFights
Indicates the total count of professional-level fights associated with an entity (such as a person or competitor).
-
D.
professionalRecordKOs
Indicates the number of times an entity has won by knockout (KOs) in its professional record.
-
E.
professionalRecordDraws
Indicates the number of times a professional competitor’s official matches have ended in a draw.
- 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_69d806a938b8819097ec43a2229fc7f9 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf21e46081908a00c9acf54f270f |
completed | April 12, 2026, 2:41 p.m. |
| PD | Predicate disambiguation | batch_69dbadfddefc81909ef7fde23b181b5c |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:42 p.m.