Triple
T29906508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japan vs Greece (2014 FIFA World Cup) |
E759549
|
entity |
| Predicate | pointsAwardedToJapan |
P62973
|
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: [Japan vs Greece (2014 FIFA World Cup), pointsAwardedToJapan, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pointsAwardedToJapan Context triple: [Japan vs Greece (2014 FIFA World Cup), pointsAwardedToJapan, 1]
-
A.
pointsAwarded
Indicates that a specified number of points has been granted to an entity as a result of some action or event.
-
B.
positionAwarded
Indicates that a specific position, role, or title has been formally granted to an entity (such as a person or organization).
-
C.
winnerPoints
Indicates the number of points earned by the winning participant or entity in a competition or event.
-
D.
isGameSpecificAward
Indicates that an award is specific to a particular game rather than being general or cross-game.
-
E.
pointsEarnedFrom
chosen
Indicates the number of points that an entity has received as a result of another specified source, action, or event.
- 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_69f224600590819085e148a01c056ef6 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f67756337881908627f7068dc02d9f |
completed | May 2, 2026, 10:14 p.m. |
| PD | Predicate disambiguation | batch_69f673c4abec8190bc2379e66f4af0a9 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 6:08 p.m.