Triple
T22251438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Capitaine Fracasse |
E549987
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Leander |
E338145
|
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: Leander | Statement: [Le Capitaine Fracasse, hasCharacter, Leander]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leander Context triple: [Le Capitaine Fracasse, hasCharacter, Leander]
-
A.
Leander
chosen
Leander is a masculine given name of Greek origin, best known from the myth of Hero and Leander.
-
B.
Geary
Geary is a small crofting settlement on the Waternish peninsula of the Isle of Skye in Scotland.
-
C.
Geary
Geary is a surname of Irish origin borne by various notable individuals across fields such as politics, sports, and the arts.
-
D.
Niles
Niles is the witty, sarcastic butler from the sitcom "The Nanny," known for his sharp one-liners and ongoing rivalry with C.C. Babcock.
-
E.
Niles
Niles is a historic former town in California, now a district of Fremont, known for its early silent film industry and railroad heritage.
- 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_69e11e41d9408190bd770cf282e22753 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f138befa208190877760dec1896740 |
completed | April 28, 2026, 10:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ab6606be48190bf16d33ca2261ca6 |
completed | May 18, 2026, 6:49 a.m. |
Created at: April 16, 2026, 8:39 p.m.