Triple
T8719133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Contemplations |
E206967
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Aurore |
E708754
|
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: Aurore | Statement: [Les Contemplations, hasPart, Aurore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aurore Context triple: [Les Contemplations, hasPart, Aurore]
-
A.
Aurore
chosen
Aurore is a French given name commonly used for women, derived from the Latin word for "dawn."
-
B.
Juliette
Juliette is a feminine given name of French origin, widely used in many countries and popularized through literature and film.
-
C.
Delphine
Delphine is an epistolary novel by Madame de Staël that explores themes of love, social convention, and women's independence in late 18th-century French society.
-
D.
Laetitia
Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
-
E.
Odile
Odile is the seductive and deceptive Black Swan character in the ballet "Swan Lake," often portrayed as the antagonist and foil to the virtuous Odette.
- 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_69ca83572d4881909bef3be2b578d539 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d014e208190a4c6055901580d0c |
completed | March 31, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf28ec7148819096f7fa33e4588b62 |
completed | April 3, 2026, 2:41 a.m. |
Created at: March 30, 2026, 6:36 p.m.