Triple
T20656660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leon Van Hove |
E507643
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Leon |
—
|
NE NERFINISHED |
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: Leon | Statement: [Leon Van Hove, givenName, Leon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leon Context triple: [Leon Van Hove, givenName, Leon]
-
A.
Leon
chosen
Leon is a masculine given name of Greek origin meaning "lion," commonly used in various cultures worldwide.
-
B.
Leon
Leon is the Galar region's undefeated Champion and a powerful Pokémon Trainer renowned as one of the strongest opponents in the Pokémon anime and games.
-
C.
Leon
Leon is the lion-themed mascot character of the Samsung Lions professional baseball team in South Korea.
-
D.
Leon
Leon is a supporting character in the Fast & Furious franchise, known as one of Dominic Toretto’s original street-racing crew members in the first film.
-
E.
Leo
Leo is a 2023 Indian Tamil-language action thriller film directed by Lokesh Kanagaraj and starring Vijay, noted for its high-octane action and connection to the Lokesh Cinematic Universe.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4bf58c081908e52a4500e03ff83 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2ed48308190b9350a323b9a7952 |
completed | April 20, 2026, 11:12 p.m. |
Created at: April 16, 2026, 11:43 a.m.