Triple
T26950829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Origin of Table Manners |
E678771
|
entity |
| Predicate | hasSeriesAuthor |
P5039
|
FINISHED |
| Object | Claude Lévi-Strauss |
—
|
NE NERFINISHED |
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: Claude Lévi-Strauss | Statement: [The Origin of Table Manners, hasSeriesAuthor, Claude Lévi-Strauss]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeriesAuthor Context triple: [The Origin of Table Manners, hasSeriesAuthor, Claude Lévi-Strauss]
-
A.
seriesAuthor
chosen
Indicates that an entity is the author or primary creator of a series (such as a book, comic, or media series).
-
B.
workInAuthorSeries
Indicates that a work is part of an author-defined series or collection.
-
C.
hasNumberOfBooksInSeries
Indicates the quantity of books that belong to a particular series.
-
D.
hasSeriesSubject
Indicates that a series is about, centers on, or thematically focuses on a particular subject.
-
E.
relatedWorkSeriesAuthor
Indicates that an author is associated with a work that is part of the same series or a related series as another work.
- 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_69eeeb4e75f08190b14fc91ca4a91488 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
Created at: April 27, 2026, 6:24 a.m.