Triple
T9183205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marie Schumann |
E220386
|
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 Schumann, givenName, Marie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marie Context triple: [Marie Schumann, 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.
Marie Émilie
Marie Émilie is a French noblewoman best known as the morganatic wife of Louis, Grand Dauphin of France, during the late 17th and early 18th centuries.
-
D.
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.
-
E.
Renée
Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
- 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_69ca83e6d77c81909862b7afef56b1bf |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccc2553e548190898434aeda517407 |
completed | April 1, 2026, 6:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d07771873c8190a9e2ebf2c83775be |
completed | April 4, 2026, 2:29 a.m. |
Created at: March 30, 2026, 7:24 p.m.