Triple
T36679461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British and Irish Lions tour to South Africa 2009 |
E905636
|
entity |
| Predicate | lionsTopTryScorer |
P173803
|
FINISHED |
| Object | Tommy Bowe |
—
|
NE NERFINISHED |
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: Tommy Bowe | Statement: [British and Irish Lions tour to South Africa 2009, lionsTopTryScorer, Tommy Bowe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lionsTopTryScorer Context triple: [British and Irish Lions tour to South Africa 2009, lionsTopTryScorer, Tommy Bowe]
-
A.
LionsTopTryScorer
chosen
Indicates that the entity is the player who scored the most tries for the Lions in a given context or competition.
-
B.
topScorer
Indicates that the subject is the individual with the highest score among a specified group or in a particular context.
-
C.
topGoalScorerGoals
Indicates the number of goals scored by the top goal scorer in a given context or competition.
-
D.
fastestGoalScorer
Indicates that the subject is the player who scored a goal in the shortest time (e.g., from match start or appearance) compared to others.
-
E.
topScorerPoints
Indicates the number of points scored by the top-scoring entity in a given context 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_69f76e7011dc819082b324f18b756a1b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c9f5a8848190ba956ff27f44e396 |
completed | May 3, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:12 p.m.