Triple
T1271331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marguerite De La Motte |
E15715
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Marguerite |
E110139
|
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: Marguerite | Statement: [Marguerite De La Motte, givenName, Marguerite]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marguerite Context triple: [Marguerite De La Motte, givenName, Marguerite]
-
A.
Marguerite
chosen
Marguerite is a French given name, equivalent to Margaret, commonly used for women and also meaning "daisy" in French.
-
B.
Marguerite De La Motte
Marguerite De La Motte was an American silent film actress best known for her leading roles in early 1920s adventure and drama films.
-
C.
Rose and Marguerite
Rose and Marguerite are the paired flowers that symbolize Saint Lucia’s cultural heritage and serve as its national floral emblem.
-
D.
Geraldine
Geraldine is a feminine given name of Germanic origin that has been borne by various notable figures, including actress Geraldine Chaplin.
-
E.
Marguerite Gaudelet
Marguerite Gaudelet was the wife of French civil engineer Gustave Eiffel, famed designer of the Eiffel Tower.
- 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_69a4935a94308190bb92555b79032824 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4c06ae7b88190a1e0b5232d84a7b1 |
completed | March 1, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad014954b08190a787d7e03e503d8d |
completed | March 8, 2026, 4:55 a.m. |
Created at: March 1, 2026, 7:50 p.m.