Triple
T13263972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emily |
E315868
|
entity |
| Predicate | hasVariantForm |
P457
|
FINISHED |
| Object | Emilie (French form) |
E199346
|
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: Emilie (French form) | Statement: [Emily, hasVariantForm, Emilie (French form)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emilie (French form) Context triple: [Emily, hasVariantForm, Emilie (French form)]
-
A.
Emilie
chosen
Emilie is a young French girl in Michael Morpurgo’s novel and its film adaptation "War Horse," who befriends and cares for the horses Joey and Topthorn during World War I.
-
B.
Élisa (French form)
Élisa is the French-language form of the feminine given name Elisa, commonly used in Francophone countries.
-
C.
Emilie François
Emilie François is an actress best known for playing Margaret Dashwood in an adaptation of Jane Austen’s "Sense and Sensibility."
-
D.
Émilie
Émilie is the given name of Gabrielle Émilie Le Tonnelier de Breteuil, marquise du Châtelet, an 18th-century French mathematician, physicist, and translator of Newton.
-
E.
Émilie
Émilie is the given first name of the French-born American actress Claudette Colbert, a major Hollywood star of the 1930s and 1940s.
- 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9901c65048190bd8b3c4872f22520 |
completed | April 11, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a48bc488190a5cf692d81bdcbba |
completed | May 3, 2026, 8:41 a.m. |
Created at: April 9, 2026, 9:25 p.m.