Triple
T3982524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The GOAT |
E86791
|
entity |
| Predicate | refersToPersonProfession |
P12884
|
FINISHED |
| Object | professional football player |
—
|
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: professional football player | Statement: [The GOAT, refersToPersonProfession, professional football player]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refersToPersonProfession Context triple: [The GOAT, refersToPersonProfession, professional football player]
-
A.
refersToPerson
Indicates that one entity is making reference to, mentioning, or pointing specifically to a particular person.
-
B.
refersToPersonKnownFor
Indicates that one entity makes reference to a person who is notable or recognized for some specific role, achievement, or characteristic.
-
C.
memberProfession
Indicates that a member or individual holds or practices a particular profession or occupation.
-
D.
namedPersonOccupation
chosen
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
E.
recognizesProfession
Indicates that one entity acknowledges or identifies another entity’s professional role or occupation as such.
- 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_69aed93fd9d4819085d3b2137d2346cb |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa3ef7ac8190abe02f440ff83c43 |
completed | March 9, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69aef8f492ac819089dbb9436dbcdd2b |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:33 p.m.