Triple
T33805892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Hardy: The Time-Torn Man |
E866384
|
entity |
| Predicate | hasAlternativeISBN |
P158138
|
FINISHED |
| Object | 9780141033869 |
—
|
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: 9780141033869 | Statement: [Thomas Hardy: The Time-Torn Man, hasAlternativeISBN, 9780141033869]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternativeISBN Context triple: [Thomas Hardy: The Time-Torn Man, hasAlternativeISBN, 9780141033869]
-
A.
hasAlternateEditionISBN
chosen
Indicates that one edition of a work is linked to another edition of the same work via its alternate ISBN.
-
B.
hasAlternativeEditionTitle
Indicates that an entity has a different or variant title used in another edition of the same work.
-
C.
haveAlternativeTitle
Indicates that an entity is known by one or more alternative titles or names in addition to its primary title.
-
D.
hasISBNAdaptation
Indicates that one work has an adaptation that is identified or cataloged by a specific ISBN.
-
E.
hasAlternativeTitleCombination
Indicates that an entity is associated with one or more alternative titles considered together as a specific combination or set.
- 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_69f3499057fc81909d862b1309a3bd71 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd5f29b1988190877764ef2a399c7f |
completed | May 8, 2026, 3:57 a.m. |
| PD | Predicate disambiguation | batch_69fd5e30194c819085b5ce586122ab37 |
completed | May 8, 2026, 3:53 a.m. |
Created at: May 1, 2026, 1:46 a.m.