Triple
T123185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Times Notable Books |
E2489
|
entity |
| Predicate | genreCoverage |
P2561
|
FINISHED |
| Object | fiction |
—
|
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: fiction | Statement: [New York Times Notable Books, genreCoverage, fiction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreCoverage Context triple: [New York Times Notable Books, genreCoverage, fiction]
-
A.
genre
Indicates the artistic or thematic category to which a work (such as a book, film, or song) belongs.
-
B.
genreDiversity
chosen
Indicates the extent to which an entity involves, includes, or spans multiple distinct genres rather than being confined to a single genre.
-
C.
fareMedia
Indicates that a particular type of ticket, pass, or payment instrument is used as the medium for paying a fare.
-
D.
mediaCoverage
Indicates that one entity reports on, documents, or broadcasts information about another entity through news or media channels.
-
E.
featuredOn
Indicates that one entity is prominently presented, highlighted, or showcased on or within another entity (such as a platform, publication, or product).
- 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_69a251b54ea88190b18281669f59b4c0 |
completed | Feb. 28, 2026, 2:23 a.m. |
| NER | Named-entity recognition | batch_69a2573b4e7481909ee09d2899f8a74b |
completed | Feb. 28, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69a2564928208190966a619680a0d6e2 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:27 a.m.