Triple
T15967222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qatar Stars League |
E387221
|
entity |
| Predicate | hasProfessionalReferees |
P120643
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Qatar Stars League, hasProfessionalReferees, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProfessionalReferees Context triple: [Qatar Stars League, hasProfessionalReferees, true]
-
A.
hasRefereesFrom
Indicates that an entity is officiated or overseen by referees originating from a specified source or location.
-
B.
overseesReferees
Indicates that one entity has responsibility for supervising, managing, or directing the work and performance of referees.
-
C.
hasProfessionalPlayers
Indicates that an entity is associated with or includes individuals who participate in a profession at a professional level.
-
D.
hasJudges
Indicates that one entity serves as a judge or panel of judges for another entity, such as an event, competition, or legal case.
-
E.
hasCourtOfficial
Indicates that an entity is associated with, employs, or is served by a court official in an official capacity.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142d6fb588190b4176eab4bbae774 |
completed | April 16, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69e173af801c8190bfc0f602831bb594 |
completed | April 16, 2026, 11:41 p.m. |
Created at: April 10, 2026, 4:54 a.m.