Triple
T2888822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dila |
E59569
|
entity |
| Predicate | plays11ASideFootball |
P42592
|
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: [Dila, plays11ASideFootball, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plays11ASideFootball Context triple: [Dila, plays11ASideFootball, true]
-
A.
playedAssociationFootball
Indicates that an entity has participated in playing the sport of association football (soccer).
-
B.
fieldSide
Indicates the relative side or position of something with respect to a defined field or playing area.
-
C.
typeOfFootball
Indicates the specific code or variant of football that characterizes or classifies a given football-related entity.
-
D.
usesNumberOfPlayersOnFieldPerTeam
Indicates that the relationship specifies or depends on how many players each team has on the field at a given time.
-
E.
league2
Indicates that an entity participates in, is a member of, or is otherwise affiliated with a specific sports league or competitive organization.
- 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_69ab4ac739188190a112f42a5a69c951 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abe04918908190aad08defd1b26d97 |
completed | March 7, 2026, 8:22 a.m. |
| PD | Predicate disambiguation | batch_69abdd15cbf08190bf7fea5ea516848a |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abdd96670c8190b727f9ac27dadf67 |
completed | March 7, 2026, 8:11 a.m. |
Created at: March 6, 2026, 10:04 p.m.