Triple
T1215839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phil Chenier |
E26103
|
entity |
| Predicate | genreOfCommentary |
P21592
|
FINISHED |
| Object | basketball analysis |
—
|
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: basketball analysis | Statement: [Phil Chenier, genreOfCommentary, basketball analysis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfCommentary Context triple: [Phil Chenier, genreOfCommentary, basketball analysis]
-
A.
hasCommentaryOn
Indicates that one entity provides commentary, explanation, or evaluative remarks about another entity.
-
B.
commentaryOn
chosen
Indicates that one entity provides evaluative or explanatory remarks about another entity, such as a work, event, or statement.
-
C.
genreOfAppearance
Indicates the genre or type of creative work in which an entity appears.
-
D.
genre
Indicates the artistic or thematic category to which a work (such as a book, film, or song) belongs.
-
E.
genreOfQuotes
Indicates that one entity is the literary, thematic, or stylistic genre to which the other entity’s quotes belong.
- 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_69a4948331fc8190b531ac9bec71c491 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be059c5c8190a200f09442c22334 |
completed | March 1, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69a4bb62a7c08190a79dcb6ff72ac99b |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.