Triple
T13778635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French rugby union championship |
E331078
|
entity |
| Predicate | usesBonusPointsFor |
P5268
|
FINISHED |
| Object | tries scored |
—
|
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: tries scored | Statement: [French rugby union championship, usesBonusPointsFor, tries scored]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBonusPointsFor Context triple: [French rugby union championship, usesBonusPointsFor, tries scored]
-
A.
usesPointsSystem
Indicates that an entity operates or functions based on a structured points-based system for evaluation, rewards, or progression.
-
B.
supportsBonus
chosen
Indicates that one entity provides or enables an additional benefit, reward, or bonus for another entity.
-
C.
rewardUse
Indicates that one entity grants or provides a reward in response to the use or utilization of another entity.
-
D.
usesPointsForLoss
Indicates that a system or rule assigns or deducts points to represent or account for a loss.
-
E.
earnsMorePointsThan
Indicates that one entity receives a greater number of points than another entity in a given context or comparison.
- 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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0239cbfc81909064ac2457fdfff5 |
completed | April 14, 2026, 9 a.m. |
| PD | Predicate disambiguation | batch_69dbbe97846c819093b00ea117b64e0d |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 10:11 p.m.