Triple
T2096427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | José Alexandre |
E32791
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Alexandre |
E42018
|
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: Alexandre | Statement: [José Alexandre, givenName, Alexandre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alexandre Context triple: [José Alexandre, givenName, Alexandre]
-
A.
Alexandre
chosen
Alexandre is a given name of Greek origin, commonly used in French and Portuguese-speaking countries as a form of Alexander.
-
B.
Édouard
Édouard is the French form of the given name Edward, commonly used in French-speaking countries.
-
C.
Maximilien
Maximilien is the given name of Maximilien Robespierre, a leading figure of the French Revolution and key architect of the Reign of Terror.
-
D.
Louis Alexandre
Louis Alexandre was a French admiral and legitimized son of King Louis XIV who became the powerful Count of Toulouse in the late 17th and early 18th centuries.
-
E.
Jean Louis
Jean Louis was a renowned French-born American costume designer celebrated for his glamorous Hollywood film and television wardrobe creations.
- 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_69a885eba0708190999696a45cbec816 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abba9b1f048190b82adfb7d8814173 |
completed | March 7, 2026, 5:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae305eabc48190b6912e05833580d8 |
completed | March 9, 2026, 2:28 a.m. |
Created at: March 4, 2026, 7:43 p.m.