Triple
T29290107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spain vs Morocco (2018 FIFA World Cup Group B) |
E742636
|
entity |
| Predicate | secondSpainGoalAwardedAfterVAR |
P193540
|
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: [Spain vs Morocco (2018 FIFA World Cup Group B), secondSpainGoalAwardedAfterVAR, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondSpainGoalAwardedAfterVAR Context triple: [Spain vs Morocco (2018 FIFA World Cup Group B), secondSpainGoalAwardedAfterVAR, true]
-
A.
secondSpainGoalScoredBy
Indicates the relationship where a specific entity is the player who scored the second goal for Spain in a given match or event.
-
B.
secondSpainGoalMethod
chosen
Indicates the method or manner by which Spain scored its second goal in a match.
-
C.
penaltyAwardedViaVAR
Indicates that a penalty decision was given after being reviewed and confirmed through the Video Assistant Referee (VAR) system.
-
D.
spainCameFromBehind
Indicates that Spain was initially trailing but later overcame the deficit to take the lead or win.
-
E.
equalisingGoalScorerForSpain
Indicates that the referenced entity is the player who scored the goal that brought Spain’s score level with their opponent.
- 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_69f0912323c48190b9a24ef8cf359225 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69fd4f39b5008190b83b3227ce22c509 |
completed | May 8, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69fd4df17c548190a4e2a6fea70f7e10 |
completed | May 8, 2026, 2:44 a.m. |
Created at: April 28, 2026, 1:01 p.m.