Triple
T13766363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yvette Monreal |
E330753
|
entity |
| Predicate | hasRole |
P161
|
FINISHED |
| Object | Gabrielle |
E302931
|
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: Gabrielle | Statement: [Yvette Monreal, hasRole, Gabrielle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gabrielle Context triple: [Yvette Monreal, hasRole, Gabrielle]
-
A.
Gabrielle
Gabrielle is the given name of Émilie du Châtelet, the renowned 18th-century French mathematician, physicist, and translator of Newton.
-
B.
Gabrielle
chosen
Gabrielle is a central character in the action film "Rambo: Last Blood," serving as John Rambo’s beloved niece whose kidnapping drives the movie’s main conflict.
-
C.
Gabrielle
Gabrielle is the birth name of the iconic French fashion designer Coco Chanel, founder of the Chanel brand.
-
D.
Gabrielle
Gabrielle is a central character in the television series "Xena: Warrior Princess," known as Xena’s loyal companion who evolves from a naive village girl into a skilled bard and warrior.
-
E.
Gabrielle
"Gabrielle" is a popular Swedish-language song by the Hootenanny Singers, known for its melodic folk-pop style and enduring appeal in Scandinavian music.
- 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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0227f2c48190983ccc9395e4e7a2 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7a864c0ac81909e5fcd134ea66414 |
completed | May 3, 2026, 7:56 p.m. |
Created at: April 9, 2026, 10:10 p.m.