Triple
T18801305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amandine Malkovich |
E459758
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Amandine |
E807875
|
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: Amandine | Statement: [Amandine Malkovich, hasGivenName, Amandine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amandine Context triple: [Amandine Malkovich, hasGivenName, Amandine]
-
A.
Amandine
chosen
Amandine is a feminine given name, primarily used in French-speaking contexts, that is closely related to and derived from the name Amanda.
-
B.
Armande
Armande is a French given name historically associated with figures in the performing arts, notably in 17th-century France.
-
C.
Aline
Aline is a feminine given name of French origin, commonly used in various cultures and languages.
-
D.
Tiphaine
Tiphaine is a French given name, notably borne by Tiphaine Auzière, the daughter of Brigitte Macron.
-
E.
Laetitia
Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
- 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a02332d88190b68feea7f2f86d06 |
completed | April 20, 2026, 3:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a055bbcb2508190a651701c4a56252f |
completed | May 14, 2026, 5:21 a.m. |
Created at: April 10, 2026, 11:53 a.m.