Triple
T11237464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Women; or, Pour et Contre |
E265977
|
entity |
| Predicate | alternativeTitleLanguage |
P35269
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Women; or, Pour et Contre, alternativeTitleLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alternativeTitleLanguage Context triple: [Women; or, Pour et Contre, alternativeTitleLanguage, French]
-
A.
alternateLanguageName
Indicates that an entity has an additional name or label in a different language from its primary or default name.
-
B.
languageOfAlternativeTitle
chosen
Indicates the language in which an alternative or variant title of an entity is expressed.
-
C.
officialTitleInLanguage
Indicates that an entity’s official title or designation is expressed in a specified language.
-
D.
alsoTranslatedAs
Indicates that something has an alternative translation or rendering in another language or form.
-
E.
titleInLanguage
Indicates that a specific title or name is expressed in a particular language.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e904cf888190826fc964f76b5cb2 |
completed | April 9, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69d7878906f48190b63ddc103a0c8f9b |
completed | April 9, 2026, 11:03 a.m. |
Created at: April 8, 2026, 9:30 p.m.