Triple
T9229061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Sullivan |
E221765
|
entity |
| Predicate | sportsField |
P887
|
FINISHED |
| Object | association football |
—
|
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: association football | Statement: [David Sullivan, sportsField, association football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportsField Context triple: [David Sullivan, sportsField, association football]
-
A.
sportsAndRecreation
Indicates a relationship where an entity is associated with, involved in, or designated for sports or recreational activities.
-
B.
sport
chosen
Indicates that an entity participates in, is associated with, or is characterized by a particular athletic activity or game.
-
C.
sportFocus
Indicates that one entity has a primary emphasis, specialization, or concentration on a particular sport represented by the other entity.
-
D.
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.
-
E.
sportSection
Indicates that something belongs to, appears in, or is categorized under the sports section of a larger collection or publication.
- 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_69ca83ec8db08190a9110df8232885d2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccdaa1c5b4819081dac6713053a8ae |
completed | April 1, 2026, 8:43 a.m. |
| PD | Predicate disambiguation | batch_69cc7a3daeb481908b0abde3fbc1f1f0 |
completed | April 1, 2026, 1:51 a.m. |
Created at: March 30, 2026, 7:29 p.m.