Triple
T11979767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tierney |
E285126
|
entity |
| Predicate | fieldOfActivityOfBearers |
P93726
|
FINISHED |
| Object | sports |
—
|
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: sports | Statement: [Tierney, fieldOfActivityOfBearers, sports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fieldOfActivityOfBearers Context triple: [Tierney, fieldOfActivityOfBearers, sports]
-
A.
occupationType
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
-
B.
occupationOfBearer
chosen
Indicates that a specified occupation or job role is held by the bearer entity.
-
C.
isAssociatedWithProfessionOfBearer
Indicates that one entity is connected to, or involved with, the profession or occupational role held by another entity.
-
D.
possibleFieldOfActivity
Indicates that something is a potential or suitable area in which an entity can operate, work, or be active.
-
E.
fieldOfCooperation
Indicates a cooperative relationship in which two or more entities work together within a particular domain, discipline, or area of 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903acbb9081908fe7f8360057785c |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902abca70819098291aa51b593708 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.