Triple
T29290218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iceland vs Croatia (2018 FIFA World Cup Group D) |
E742639
|
entity |
| Predicate | equaliserScorer |
P99876
|
FINISHED |
| Object | Gylfi Sigurðsson |
—
|
NE NERFINISHED |
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: Gylfi Sigurðsson | Statement: [Iceland vs Croatia (2018 FIFA World Cup Group D), equaliserScorer, Gylfi Sigurðsson]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equaliserScorer Context triple: [Iceland vs Croatia (2018 FIFA World Cup Group D), equaliserScorer, Gylfi Sigurðsson]
-
A.
finalEqualiserScorer
chosen
Indicates that the subject is the player who scored the final goal that brought the scores level in a match.
-
B.
equalisingGoalTeam
Indicates that a team scores a goal which brings the score level with the opposing team.
-
C.
equalizingGoalBy
Indicates that one entity has the objective of reducing differences or disparities between itself and another entity.
-
D.
scoringAverage
Indicates the typical or mean score achieved by an entity over a series of attempts, events, or performances.
-
E.
EloRating
Indicates a competitive skill rating assigned to an entity, typically updated over time based on performance against other rated entities.
- 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_69f6653fd31c8190af982a019dfe645e |
completed | May 2, 2026, 8:57 p.m. |
| PD | Predicate disambiguation | batch_69f663362c008190a22afed262f1e426 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 1:01 p.m.