Triple
T6717079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marie de Jongh Woolf |
E153296
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Marie |
E27948
|
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: Marie | Statement: [Marie de Jongh Woolf, givenName, Marie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marie Context triple: [Marie de Jongh Woolf, givenName, Marie]
-
A.
Marie
chosen
Marie is a widely used European given name, especially common in French-speaking countries, derived from the Hebrew name Miryam (Mary).
-
B.
Marie Christine
Marie Christine, better known as Princess Michael of Kent, is a member of the British royal family, an author, and the wife of Prince Michael of Kent, a first cousin of King Charles III.
-
C.
Françoise
Françoise is the given name of Louise de La Vallière, a 17th-century French noblewoman best known as a mistress of King Louis XIV.
-
D.
Renée
Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
-
E.
Louise-Marie
Louise-Marie is a French royal given name notably borne by Princess Louise-Marie of Orléans, a 19th-century Belgian queen consort.
- 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_69c68809b4608190a2509ddb5ab87f05 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d125db3c8190aad28919226a16da |
completed | March 27, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c751088fc08190abc2eacfb95867f3 |
completed | March 28, 2026, 3:54 a.m. |
Created at: March 27, 2026, 2:07 p.m.