Triple
T13607089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mazarine Pingeot |
E325089
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Mazarine |
E325088
|
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: Mazarine | Statement: [Mazarine Pingeot, givenName, Mazarine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mazarine Context triple: [Mazarine Pingeot, givenName, Mazarine]
-
A.
Mazarine
chosen
Mazarine is a French writer, academic, and media figure best known as the once-secret daughter of former French President François Mitterrand.
-
B.
Dunkerquoise
Dunkerquoise is the French demonym referring to a female inhabitant or native of the port city of Dunkirk in northern France.
-
C.
L’Azur
L’Azur is a celebrated poem by Stéphane Mallarmé, noted for its symbolist exploration of the sky, the infinite, and existential anguish.
-
D.
Tavernier Blue
Tavernier Blue was a large, deep-blue diamond of Indian origin that was famously acquired by French gem merchant Jean-Baptiste Tavernier and later recut into what is now known as the Hope Diamond.
-
E.
Borouge
Borouge is a leading petrochemicals company based in the United Arab Emirates, specializing in the production of polyolefins for packaging, infrastructure, and industrial applications.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb07e442c819086a8cbb967c03ad3 |
completed | April 12, 2026, 2:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78ae56e2081909c0fd044ce3730a9 |
completed | May 3, 2026, 5:50 p.m. |
Created at: April 9, 2026, 9:50 p.m.