Triple
T8693239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vivienne Marcheline Jolie-Pitt |
E206341
|
entity |
| Predicate | middleName |
P143
|
FINISHED |
| Object | Marcheline |
E751010
|
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: Marcheline | Statement: [Vivienne Marcheline Jolie-Pitt, middleName, Marcheline]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marcheline Context triple: [Vivienne Marcheline Jolie-Pitt, middleName, Marcheline]
-
A.
Marcheline
chosen
Marcheline is the affectionate nickname of Marcheline Bertrand, an American actress and humanitarian best known as the mother of Angelina Jolie.
-
B.
Marcelle
Marcelle is a given name, typically a feminine form of Marcel, used in various cultures.
-
C.
Micheline
Micheline is a feminine given name of French origin, commonly used in French-speaking countries.
-
D.
Madelaine
Madelaine is a character in the Danish crime thriller film "The Salvation."
-
E.
Martine
Martine is a feminine given name commonly used in French- and English-speaking countries.
- 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_69ca835481fc819084e33d3bc883bfa6 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5826bbb48190a212fb1bb06e05e6 |
completed | March 31, 2026, 11:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf28958ba481908383e31802ce2093 |
completed | April 3, 2026, 2:40 a.m. |
Created at: March 30, 2026, 6:33 p.m.