Triple
T18335855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lee Haney |
E439267
|
entity |
| Predicate | yearsActiveAsProfessionalBodybuilder |
P34676
|
FINISHED |
| Object | 1980s |
—
|
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: 1980s | Statement: [Lee Haney, yearsActiveAsProfessionalBodybuilder, 1980s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearsActiveAsProfessionalBodybuilder Context triple: [Lee Haney, yearsActiveAsProfessionalBodybuilder, 1980s]
-
A.
activeYearsInSport
Indicates the span of years during which an entity actively participated in a particular sport.
-
B.
yearsActiveInMMA
Indicates the span of time, in years, during which an entity has been actively involved in mixed martial arts competition or participation.
-
C.
yearsActiveAsBoxer
Indicates the span of time, measured in years, during which an individual was actively engaged in boxing.
-
D.
MrOlympiaChampionYear
Indicates that the subject is the winner of the Mr. Olympia bodybuilding competition in the specified year.
-
E.
activeInYears
chosen
Indicates that an entity was active or operational during the specified years or year range.
- 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_69d8b9175fec8190af865699b4e64d8c |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50ecd759481909703ed2d0d68199f |
completed | April 19, 2026, 5:20 p.m. |
| PD | Predicate disambiguation | batch_69e44fe91bc08190906518e1b120fcf0 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:37 a.m.