Triple
T31868610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barry Hawkins |
E813529
|
entity |
| Predicate | hasHighestProfessionalBreak |
P196706
|
FINISHED |
| Object | 147 |
—
|
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: 147 | Statement: [Barry Hawkins, hasHighestProfessionalBreak, 147]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighestProfessionalBreak Context triple: [Barry Hawkins, hasHighestProfessionalBreak, 147]
-
A.
hasRankAtPeakOfCareer
Indicates the specific rank or position an entity held at the highest point of its career.
-
B.
hasWonProfessionalTournament
Indicates that an entity has achieved victory in at least one professional-level tournament or competition.
-
C.
hasHighest
Indicates that one entity possesses the greatest value, rank, or level in a specified attribute or set compared to all others.
-
D.
hasHighestPoints
Indicates that the subject entity possesses the greatest number of points compared to all relevant others in the given context.
-
E.
madeMaximumBreakIn
Indicates that the subject achieved the highest possible break (maximum scoring run) in a snooker frame or 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_69f348ecb07481909c8f72619131b115 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe629b4fa481908467c7c41b77f0c6 |
completed | May 8, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69fe61bb260c819083f9378a3a06ca47 |
completed | May 8, 2026, 10:20 p.m. |
| PDg | Predicate description generation | batch_69fe629a8d4c8190b4aa4dee39efc0a6 |
completed | May 8, 2026, 10:24 p.m. |
Created at: April 30, 2026, 11:54 p.m.