Triple
T2831501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danielle Mitterrand |
E62247
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Danielle |
E184707
|
NE 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: Danielle | Statement: [Danielle Mitterrand, givenName, Danielle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Danielle Context triple: [Danielle Mitterrand, givenName, Danielle]
-
A.
Danielle
chosen
"Danielle" is a work created by Sarah Churchill, known as part of her contributions to the arts.
-
B.
Nicole
Nicole is a central character in Margaret Atwood's dystopian novel "The Testaments," whose story helps expose and challenge the oppressive regime of Gilead.
-
C.
Jenna
Jenna is a common feminine given name, often used as a diminutive or variant of Jennifer.
-
D.
Adrienne
Adrienne is a feminine given name of French origin, commonly used in English- and French-speaking countries.
-
E.
Madelaine
Madelaine is a character in the Danish crime thriller film "The Salvation."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ab4c3c39188190955b9c49d98463d8 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdebd5a2c81908f0e30a0ae0eb8df |
completed | March 7, 2026, 8:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afceb771d48190a1467a6e58f756ad |
completed | March 10, 2026, 7:56 a.m. |
Created at: March 6, 2026, 10:01 p.m.