Triple
T34863842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Lamp and the Bell |
E1004954
|
entity |
| Predicate | isWrittenByFemaleAuthor |
P178886
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [The Lamp and the Bell, isWrittenByFemaleAuthor, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isWrittenByFemaleAuthor Context triple: [The Lamp and the Bell, isWrittenByFemaleAuthor, true]
-
A.
writtenByWoman
chosen
Indicates that the work or content in question was authored or created by a female individual.
-
B.
hasAuthorGender
Indicates that an entity (such as a work or publication) is associated with an author of a specified gender.
-
C.
notWrittenBy
Indicates that a specified work or content is explicitly not authored or created by a given entity.
-
D.
actuallyWrittenBy
Indicates that the specified work was in fact authored by the given entity, possibly correcting or overriding a previously assumed or credited author.
-
E.
hasFemaleCharacter
Indicates that an entity includes or features at least one female character.
- 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_69f76dbb678081909a247b9b5e1a73ac |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782f4f10081908f97f6d0d2dbeec7 |
completed | May 3, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69f780ff71cc8190a67e71076fbad81a |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.