Triple
T25002360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International 12-metre rule |
E625747
|
entity |
| Predicate | classRating |
P157903
|
FINISHED |
| Object | 12 metres |
—
|
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: 12 metres | Statement: [International 12-metre rule, classRating, 12 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: classRating Context triple: [International 12-metre rule, classRating, 12 metres]
-
A.
ratingCategory
Indicates the qualitative classification or level assigned to a rating (e.g., low, medium, high) within an evaluation or scoring system.
-
B.
ratingContext
Indicates the situational or contextual factors under which a rating is given or applies.
-
C.
ratingSystem
Indicates a system or method used to assign evaluative scores or rankings to items, actions, or entities based on defined criteria.
-
D.
rating
Indicates an evaluation relationship where one entity assigns a qualitative or quantitative score or judgment to another entity.
-
E.
ratingOfWork
Indicates the evaluative score or assessment assigned to a particular work or creation.
- 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_69e2ff26c50481908bc82e799c9e6587 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f453035f508190be83a3d521723acf |
completed | May 1, 2026, 7:15 a.m. |
| PD | Predicate disambiguation | batch_69f44d77f6e88190a4643ab2cbef567b |
completed | May 1, 2026, 6:51 a.m. |
| PDg | Predicate description generation | batch_69f45300bd488190bb1d4160f5534ef6 |
completed | May 1, 2026, 7:15 a.m. |
Created at: April 18, 2026, 6:05 a.m.