Triple
T34637791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herbert Lawford |
E889476
|
entity |
| Predicate | inSportDiscipline |
P179726
|
FINISHED |
| Object | singles tennis |
—
|
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: singles tennis | Statement: [Herbert Lawford, inSportDiscipline, singles tennis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inSportDiscipline Context triple: [Herbert Lawford, inSportDiscipline, singles tennis]
-
A.
sportDisciplineScope
Indicates the specific sport discipline or category within which a given relationship, rule, or activity is defined or applies.
-
B.
esportDiscipline
Indicates that one entity is a specific esports game or discipline in which the other entity participates or is involved.
-
C.
WorldCupDiscipline
Indicates a disciplinary action (such as a card, suspension, or sanction) imposed on an entity in the context of a FIFA World Cup competition.
-
D.
sportEventType
Indicates the specific kind or category of sport associated with a given sporting event.
-
E.
sportCategory
Indicates that one entity is classified as a type or category of sport to which the other entity (typically a specific sport or sporting event) belongs.
- F. None of above. chosen
Provenance (4 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_69f349d724848190b63ad3407e0006d9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7238172748190b8cd340ad1f4ba80 |
completed | May 3, 2026, 10:29 a.m. |
| PD | Predicate disambiguation | batch_69f72155c48881909bd40b9aa3febd5a |
completed | May 3, 2026, 10:20 a.m. |
| PDg | Predicate description generation | batch_69f72349f1108190b6a06758ab2f40bb |
completed | May 3, 2026, 10:28 a.m. |
Created at: May 1, 2026, 2:04 a.m.