Triple
T35771742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nate Marquardt |
E1034179
|
entity |
| Predicate | careerAttribute |
P138237
|
FINISHED |
| Object | long tenure in top-level MMA |
—
|
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: long tenure in top-level MMA | Statement: [Nate Marquardt, careerAttribute, long tenure in top-level MMA]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerAttribute Context triple: [Nate Marquardt, careerAttribute, long tenure in top-level MMA]
-
A.
professionAttribute
Indicates that a specific attribute, quality, or characteristic is associated with a given profession.
-
B.
coreAttribute
Indicates that one attribute is a fundamental, defining, or essential property of another entity.
-
C.
workAttribute
Indicates that a particular characteristic, quality, or property is associated with a specific work or piece of work.
-
D.
employmentCharacteristic
chosen
Indicates a specific attribute, condition, or quality associated with a person’s employment or job situation.
-
E.
skillFactor
Indicates the degree or level of skill associated with an entity in performing a particular task 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_69f76e13edd081909101629aa829c4ad |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a1f85ddc8190af4cb53e19acd508 |
completed | May 3, 2026, 7:28 p.m. |
| PD | Predicate disambiguation | batch_69f7a070e23881909a233370acb57384 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:06 p.m.