Triple
T25797130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phil O’Donnell Stand |
E649716
|
entity |
| Predicate | namedForPersonOccupation |
P117536
|
FINISHED |
| Object | professional footballer |
—
|
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 footballer | Statement: [Phil O’Donnell Stand, namedForPersonOccupation, professional footballer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedForPersonOccupation Context triple: [Phil O’Donnell Stand, namedForPersonOccupation, professional footballer]
-
A.
namedPersonOccupation
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
B.
namedPersonRole
Indicates that a person is identified by name as holding a specific role or position in a given context.
-
C.
namedAfterOccupationOrRole
chosen
Indicates that an entity is named after a specific occupation, profession, or social role associated with a person or group.
-
D.
namedForPersonAffiliation
Indicates that something is named after a person specifically because of that person's affiliation with a particular group, organization, place, or role.
-
E.
namesakeOccupation
Indicates that one entity’s occupation is the same as, or derived from, the occupation associated with the other entity’s namesake.
- 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_69e7ab34f8c8819099f6c4dabdabf129 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f60c3b09488190ade1b69ff7f0df0e |
completed | May 2, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f60b8461ac81908c5bd3d73eed59f4 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 22, 2026, 6:32 a.m.