Triple
T29710470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Germany vs Sweden (2018 FIFA World Cup) |
E751763
|
entity |
| Predicate | GermanyPointsFromMatch |
P171060
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Germany vs Sweden (2018 FIFA World Cup), GermanyPointsFromMatch, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: GermanyPointsFromMatch Context triple: [Germany vs Sweden (2018 FIFA World Cup), GermanyPointsFromMatch, 3]
-
A.
SwedenPointsFromMatch
Indicates the number of points Sweden obtained from a specific match.
-
B.
resultOfMatch
Indicates that one entity is the outcome or product produced by a particular match or matching event involving another entity.
-
C.
CroatiaPointsAfterMatch
Indicates the number of points Croatia has accumulated immediately following a specific match.
-
D.
scoredInMatch
Indicates that an entity (typically a player or team) scored during a particular match.
-
E.
IcelandPointsAfterMatch
Indicates the number of points Iceland has accumulated immediately following a specific match.
- 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_69f0d62748848190b030d0a703629a7d |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f698ad83a08190a6834056ccc3e3a4 |
completed | May 3, 2026, 12:37 a.m. |
| PD | Predicate disambiguation | batch_69f69664142c8190bc695501056b0236 |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f697e92e2c8190bed50d5ba0981b64 |
completed | May 3, 2026, 12:33 a.m. |
Created at: April 28, 2026, 7:30 p.m.