Triple
T18825067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Heir Apparent: Largo Winch |
E460362
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Léa |
E641135
|
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: Léa | Statement: [The Heir Apparent: Largo Winch, character, Léa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Léa Context triple: [The Heir Apparent: Largo Winch, character, Léa]
-
A.
Léa
chosen
Léa is a French feminine given name commonly used in Francophone countries.
-
B.
Nathalie
Nathalie is a feminine given name of French origin commonly used in many European and French-speaking countries.
-
C.
Laetitia
Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
-
D.
Mélanie
Mélanie is a feminine given name of French origin commonly used in French-speaking countries.
-
E.
Aline
Aline is a feminine given name of French origin, commonly used in various cultures and languages.
- 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_69d8dcf94c288190a06dea029ae4b223 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a6bdefac8190892d6fd5c20a431e |
completed | April 20, 2026, 4:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0575ac249c8190989b9de40eb8a444 |
completed | May 14, 2026, 7:11 a.m. |
Created at: April 10, 2026, 11:56 a.m.