Triple
T23521981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Germany vs Hungary (UEFA Euro 2020 Group F) |
E574531
|
entity |
| Predicate | awayTeamHalftimeScore |
P25689
|
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: [Germany vs Hungary (UEFA Euro 2020 Group F), awayTeamHalftimeScore, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awayTeamHalftimeScore Context triple: [Germany vs Hungary (UEFA Euro 2020 Group F), awayTeamHalftimeScore, 1]
-
A.
halftimeScore
Indicates the score or result of a game or match at the halfway point (halftime).
-
B.
awayTeamPointsInFirstHalf
Indicates the number of points scored by the away team during the first half of a game.
-
C.
homeTeamPointsInFirstHalf
Indicates the number of points scored by the home team during the first half of a game.
-
D.
awayTeamGoalsFirstHalf
chosen
Indicates the number of goals scored by the away team during the first half of a match.
-
E.
awayTeamGoalsSecondHalf
Indicates the number of goals scored by the away 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_69e245bb3dcc8190ba9a2b35972b58d0 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1aa873ad48190a86807bd4f26df82 |
completed | April 29, 2026, 6:51 a.m. |
| PD | Predicate disambiguation | batch_69f1189d75b48190a1c01928a993c9fb |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:08 p.m.