Triple
T18573252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landes |
E453922
|
entity |
| Predicate | contains |
P35
|
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: [Landes, contains, Leon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leon Context triple: [Landes, contains, Leon]
-
A.
Leon
chosen
Leon is a masculine given name of Greek origin meaning "lion," commonly used in various cultures worldwide.
-
B.
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.
-
C.
Leo
Leo is the first name of Dr. Leo Marvin, the uptight psychiatrist character from the comedy film "What About Bob?".
-
D.
Leo
Leo is a masculine given name of Latin origin meaning "lion," historically borne by popes, saints, and rulers.
-
E.
Leo
Leo is a central character in the wuxia film "House of Flying Daggers," known for his complex loyalties and pivotal role in the story’s romantic and political intrigue.
- 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e543c7f63c81909b5d5764ffd20234 |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 11:43 a.m.