Triple
T4520431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Whole Town’s Talking |
E103251
|
entity |
| Predicate | hasISBN13 |
P3840
|
FINISHED |
| Object | 9781400065950 |
—
|
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: 9781400065950 | Statement: [The Whole Town’s Talking, hasISBN13, 9781400065950]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasISBN13 Context triple: [The Whole Town’s Talking, hasISBN13, 9781400065950]
-
A.
isbn13
chosen
Indicates that the subject has the specified 13-digit International Standard Book Number (ISBN-13) as its unique identifier.
-
B.
isbn
Indicates that a publication is associated with a specific International Standard Book Number (ISBN) that uniquely identifies it.
-
C.
isbnType
Indicates the specific classification or format type associated with an ISBN identifier for a publication.
-
D.
hasGoodreadsId
Indicates that an entity is associated with a specific identifier used by Goodreads to uniquely reference it in their system.
-
E.
containsBook
Indicates that one entity (typically a container or collection) includes a specific book as part of its contents.
- 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_69bd43dba59881908cf59b31df8c7ae1 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5749d95481908db0176459c096cf |
completed | March 20, 2026, 2:18 p.m. |
| PD | Predicate disambiguation | batch_69bd521abea48190b3e758a1f98dd55e |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:02 p.m.