Triple
T32093134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2017 British & Irish Lions tour to New Zealand |
E819647
|
entity |
| Predicate | LionsTopPointScorer |
P6605
|
FINISHED |
| Object | Leigh Halfpenny |
—
|
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: Leigh Halfpenny | Statement: [2017 British & Irish Lions tour to New Zealand, LionsTopPointScorer, Leigh Halfpenny]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: LionsTopPointScorer Context triple: [2017 British & Irish Lions tour to New Zealand, LionsTopPointScorer, Leigh Halfpenny]
-
A.
leagueLeadingStatistic
Indicates that an entity holds the top value in a particular statistical category within a specified league.
-
B.
topScorer
chosen
Indicates that the subject is the individual with the highest score among a specified group or in a particular context.
-
C.
seasonTopScorerTeam1
Indicates that the referenced entity is the team whose player was the top scorer for team 1 in a given season.
-
D.
isAmongTopScorers
Indicates that an entity ranks within the highest-performing group based on a scoring or evaluation metric.
-
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_69f349004b2481908ce2e50af0d579a8 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b63f9da88190975712a5644500c7 |
completed | May 3, 2026, 2:43 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a7bdb481908d16a32f49e38c2c |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:25 a.m.