Triple
T10176736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Simone Mareuil |
E235871
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Simone |
E152444
|
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: Simone | Statement: [Simone Mareuil, givenName, Simone]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Simone Context triple: [Simone Mareuil, givenName, Simone]
-
A.
Simone
chosen
Simone is a feminine given name of Hebrew origin meaning "hearkening" or "one who listens," widely used across various cultures.
-
B.
Simone Tata
Simone Tata is an Indian businesswoman best known for transforming Lakmé into a leading cosmetics brand and playing a key role in the Tata Group’s consumer business expansion.
-
C.
Simone Kahn
Simone Kahn was a French intellectual and early supporter of the Surrealist movement, known for her close involvement with avant-garde circles in Paris in the 1920s.
-
D.
Nadine
"Nadine" is a classic 1964 rock and roll song by Chuck Berry, known for its vivid storytelling and driving guitar riff.
-
E.
Nadine
Nadine is a feminine given name used in various cultures, often associated with the meaning "hope."
- 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_69ca84d1d5f88190ab878a1021ecff68 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdecd3a2688190bce277bffffcbf8b |
completed | April 2, 2026, 4:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d301232e5c8190ad80c4e78681994c |
completed | April 6, 2026, 12:41 a.m. |
Created at: March 30, 2026, 9:11 p.m.