Triple
T5786441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeu de paume |
E128278
|
entity |
| Predicate | rulesFeature |
P9789
|
FINISHED |
| Object | scoring system similar to tennis |
—
|
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: scoring system similar to tennis | Statement: [Jeu de paume, rulesFeature, scoring system similar to tennis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rulesFeature Context triple: [Jeu de paume, rulesFeature, scoring system similar to tennis]
-
A.
formsFeature
chosen
Indicates that one entity constitutes or creates a characteristic, component, or distinguishing element of another entity.
-
B.
administrativeFeature
Indicates that one entity serves as an administrative or governance-related feature, function, or attribute associated with another entity.
-
C.
protectsFeature
Indicates that one entity safeguards, preserves, or defends a particular feature or characteristic of another entity.
-
D.
featureType
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
-
E.
featuresLaw
Indicates that something includes, presents, or is characterized by a particular law or legal provision.
- 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_69c0084450048190bc647b649a05136b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02a1c29d48190af36cc855bb491dd |
completed | March 22, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_69c021d2cd608190b98a7e3aa7001d27 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:51 p.m.