Triple
T28926649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin Atkinson |
E733665
|
entity |
| Predicate | hasGivenYellowCardsTo |
P167935
|
FINISHED |
| Object | various Premier League players |
—
|
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: various Premier League players | Statement: [Martin Atkinson, hasGivenYellowCardsTo, various Premier League players]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGivenYellowCardsTo Context triple: [Martin Atkinson, hasGivenYellowCardsTo, various Premier League players]
-
A.
hasGivenRedCardsTo
Indicates that one entity has issued or awarded red cards to another entity, typically in a disciplinary or officiating context.
-
B.
numberOfYellowCards
Indicates the count of yellow cards assigned to an entity (such as a player or team) within a specified context or event.
-
C.
numberOfRedCards
Indicates the count of red cards associated with a given entity or event.
-
D.
minuteOfRedCard
Indicates the specific minute in a match when a red card was issued.
-
E.
playerSentOff
Indicates that a player has been dismissed from the game, typically due to a serious rule violation, and is no longer allowed to participate.
- 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_69f05b0b49b08190b8994b339c7980f6 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f66e5f7e30819094530abceabd5f43 |
completed | May 2, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66d75a8788190aa9ca2c977429045 |
completed | May 2, 2026, 9:32 p.m. |
Created at: April 28, 2026, 8:24 a.m.