Triple
T33431612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japan vs South Africa (2015 Rugby World Cup) |
E856144
|
entity |
| Predicate | JapanPointsFromTriesAndConversions |
P178103
|
FINISHED |
| Object | 21 |
—
|
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: 21 | Statement: [Japan vs South Africa (2015 Rugby World Cup), JapanPointsFromTriesAndConversions, 21]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: JapanPointsFromTriesAndConversions Context triple: [Japan vs South Africa (2015 Rugby World Cup), JapanPointsFromTriesAndConversions, 21]
-
A.
touchdownPoints
Indicates the number of points awarded to a team for successfully scoring a touchdown in a game.
-
B.
JetsScore
Indicates that the team named Jets scores a certain number of points in a game or event.
-
C.
worldCupTriesTotal
Indicates the total number of tries an entity has scored across all Rugby World Cup matches.
-
D.
totalPointsScored
Indicates the total number of points accumulated or scored by an entity over a defined period, event, or context.
-
E.
topTryScorer
Indicates that the subject is the player who scored the highest number of tries in a given competition, season, or context.
- 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_69f349709e7881908c342b4d34f555f4 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70c53062c8190b4cb7be22ab00bc7 |
completed | May 3, 2026, 8:50 a.m. |
| PD | Predicate disambiguation | batch_69f70abe43e08190b2a30930d96247c1 |
completed | May 3, 2026, 8:43 a.m. |
| PDg | Predicate description generation | batch_69f70b94784c8190970d654e066eb50d |
completed | May 3, 2026, 8:47 a.m. |
Created at: May 1, 2026, 1:36 a.m.