Triple
T28226983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Femme à la Robe Verte |
E711614
|
entity |
| Predicate | subjectHasFullName |
P16
|
FINISHED |
| Object | Camille Doncieux |
—
|
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: Camille Doncieux | Statement: [La Femme à la Robe Verte, subjectHasFullName, Camille Doncieux]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectHasFullName Context triple: [La Femme à la Robe Verte, subjectHasFullName, Camille Doncieux]
-
A.
fullName
chosen
Indicates that an entity has a complete personal name, typically combining given name(s) and family name into a single string.
-
B.
fullNameRevealed
Indicates that an entity’s complete personal name has been disclosed or made known to another party or in a given context.
-
C.
namedForPersonFullName
Indicates that an entity is named after a specific person, identified by that person’s full name.
-
D.
typicalFullName
Indicates that the object is the standard or commonly used full name associated with the subject.
-
E.
hasFullNameInWork
Indicates that an entity is referred to by a specific full name within a particular work or publication.
- 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_69efb51dfb048190ada79b745c33b363 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f6db1f3ec48190a82e7d893d3c76ba |
completed | May 3, 2026, 5:20 a.m. |
| PD | Predicate disambiguation | batch_69f6d82adfa481908a5e196d2e18c73f |
completed | May 3, 2026, 5:07 a.m. |
Created at: April 27, 2026, 10:50 p.m.