Triple
T29290002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portugal vs Spain (2018 FIFA World Cup Group B) |
E742634
|
entity |
| Predicate | equalisingGoalScorerForSpain |
P166801
|
FINISHED |
| Object | Diego Costa |
—
|
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: Diego Costa | Statement: [Portugal vs Spain (2018 FIFA World Cup Group B), equalisingGoalScorerForSpain, Diego Costa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equalisingGoalScorerForSpain Context triple: [Portugal vs Spain (2018 FIFA World Cup Group B), equalisingGoalScorerForSpain, Diego Costa]
-
A.
SpainGoals
Indicates the number of goals scored by Spain in a given match or competition context.
-
B.
ChelseaGoals
Indicates that the event or record involves goals scored by the football club Chelsea.
-
C.
Jorge Garbajosa_position
Indicates the playing position or role that Jorge Garbajosa occupies in his sport.
-
D.
SupercopaDeEspañaTitles
Indicates the number of Supercopa de España titles an entity has won.
-
E.
goalsByRealMadrid
Indicates the number of goals that were scored by Real Madrid.
- 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_69f0912323c48190b9a24ef8cf359225 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f6653e73e081908ea14f73f88d5648 |
completed | May 2, 2026, 8:57 p.m. |
| PD | Predicate disambiguation | batch_69f660f2e3708190ab658652bcfc04d0 |
completed | May 2, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69f661e9cb308190a56e25dc17df248e |
completed | May 2, 2026, 8:43 p.m. |
Created at: April 28, 2026, 1:01 p.m.