Triple
T19437394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Parisian Woman |
E486257
|
entity |
| Predicate | hasMainCharacter |
P1183
|
FINISHED |
| Object | Jeanette |
—
|
NE NERFINISHED |
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: Jeanette | Statement: [The Parisian Woman, hasMainCharacter, Jeanette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeanette Context triple: [The Parisian Woman, hasMainCharacter, Jeanette]
-
A.
Jeanette
Jeanette is the given first name of American actress Janet Leigh, famed for her role in Alfred Hitchcock’s film "Psycho."
-
B.
Jeanette
Jeanette is the given first name of American actress Peggy Moran, known for her roles in 1930s and 1940s Hollywood films.
-
C.
Jeanette
Jeanette is the given name of Jennie Jerome, the American-born British socialite best known as the mother of Winston Churchill.
-
D.
Jeanette
chosen
Jeanette is a Spanish-British singer and actress best known for her soft, melancholic pop songs that became iconic in the Spanish-speaking world during the 1970s.
-
E.
Janette
Janette is a feminine given name of English origin, often considered a diminutive or variant of Janet or Jane.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633618c2881908f3d2a9cabb02289 |
completed | April 20, 2026, 2:08 p.m. |
Created at: April 10, 2026, 1:38 p.m.