Triple
T8573986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knox Léon Jolie-Pitt |
E202999
|
entity |
| Predicate | middleName |
P143
|
FINISHED |
| Object | Léon |
E675966
|
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: Léon | Statement: [Knox Léon Jolie-Pitt, middleName, Léon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Léon Context triple: [Knox Léon Jolie-Pitt, middleName, Léon]
-
A.
Léon
Léon is a traditional cultural and historical region in northwestern Brittany, France, known for its distinct Breton heritage and coastal landscapes.
-
B.
Léon
chosen
Léon is a masculine given name of French origin, commonly used in French-speaking countries and derived from the Latin name Leo, meaning "lion."
-
C.
Léon
Léon is a French surname borne by various notable individuals across fields such as politics, arts, and academia.
-
D.
Léon: The Professional
Léon: The Professional is a 1994 crime thriller film by Luc Besson about a hitman who forms an unusual bond with a young girl after her family is murdered.
-
E.
Le Fel
Le Fel is a commune in southern France whose name is borne by the Entraygues-le-Fel Appellation d'Origine Contrôlée wine region.
- 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_69ca8328ebe481909a8c038fa79959b4 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbea458c1081908e79bee2cbf97207 |
completed | March 31, 2026, 3:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce898cf8648190b52758b6ecf2959b |
completed | April 2, 2026, 3:21 p.m. |
Created at: March 30, 2026, 6:21 p.m.