Triple
T735157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goodreads Choice Award for Memoir & Autobiography 2020 |
E14912
|
entity |
| Predicate | languageOfMostNominations |
P19541
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Goodreads Choice Award for Memoir & Autobiography 2020, languageOfMostNominations, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfMostNominations Context triple: [Goodreads Choice Award for Memoir & Autobiography 2020, languageOfMostNominations, English]
-
A.
mostNominationsCount
Indicates the highest number of nominations that any entity in the relevant set has received.
-
B.
officialLanguageOfNomination
Indicates the language officially used in the nomination process or documentation for a given entity.
-
C.
awardNameLanguage
Indicates the language in which the name of an award is expressed.
-
D.
mostNominationsFilm
Indicates that a film holds the highest number of nominations within a given set, context, or award event.
-
E.
typicalNumberOfNominees
Indicates the usual or standard count of nominees associated with something, such as an award, position, or selection process.
- 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_69a4934d9930819099eed80096b0597d |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a66820548190b373deb117187c2c |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a4fafee081909bf356854c09aaff |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a66658948190bdae6e521951954f |
completed | March 1, 2026, 8:49 p.m. |
Created at: March 1, 2026, 7:37 p.m.