Triple
T1154007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevin Terry |
E23740
|
entity |
| Predicate | typeOfOfficial |
P5518
|
FINISHED |
| Object | referee |
—
|
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: referee | Statement: [Kevin Terry, typeOfOfficial, referee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfOfficial Context triple: [Kevin Terry, typeOfOfficial, referee]
-
A.
typeOfOffice
Indicates the specific category or kind of office that an office entity belongs to (e.g., executive, legislative, judicial, or other office types).
-
B.
typeOfRole
chosen
Indicates that one entity specifies the kind or category of role that another entity holds or performs.
-
C.
isOfficerOf
Indicates that one entity holds an official position, role, or office within another entity (such as an organization, group, or institution).
-
D.
typeOfPolitician
Indicates that one politician belongs to a specific category or role of political office (e.g., senator, mayor, minister) within a political system.
-
E.
personnelType
Indicates the classification or role category assigned to a person within an organization or system.
- 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_69a493f0d32c8190ac74bad3c87f2641 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bc8e9cb481908a528a828b21d497 |
completed | March 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69a4bb50d19c81908a98dbbb04a8906f |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.