Triple
T23528472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hungary vs France (UEFA Euro 2020 Group F) |
E576496
|
entity |
| Predicate | homeTeamFirstHalfScore |
P25688
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Hungary vs France (UEFA Euro 2020 Group F), homeTeamFirstHalfScore, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: homeTeamFirstHalfScore Context triple: [Hungary vs France (UEFA Euro 2020 Group F), homeTeamFirstHalfScore, 1]
-
A.
homeTeamPointsInFirstHalf
Indicates the number of points scored by the home team during the first half of a game.
-
B.
homeTeamGoalsFirstHalf
chosen
Indicates the number of goals scored by the home team during the first half of a match.
-
C.
awayTeamGoalsFirstHalf
Indicates the number of goals scored by the away team during the first half of a match.
-
D.
awayTeamPointsInFirstHalf
Indicates the number of points scored by the away team during the first half of a game.
-
E.
homeTeamGoalsSecondHalf
Indicates the number of goals scored by the home team during the second half of a match.
- 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_69e245f5a8848190a2ba42e271c6c31f |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1ac758038819098f5f597be39274e |
completed | April 29, 2026, 7 a.m. |
| PD | Predicate disambiguation | batch_69f1189d75b48190a1c01928a993c9fb |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:09 p.m.