Triple
T4820845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luc Tuymans |
E107706
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Luc |
E216416
|
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: Luc | Statement: [Luc Tuymans, givenName, Luc]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luc Context triple: [Luc Tuymans, givenName, Luc]
-
A.
Luc
chosen
Luc is the given name of Luc Longley, the Australian former professional basketball player and three-time NBA champion with the Chicago Bulls.
-
B.
Lou
Lou is a character from the virtual reality co-op shooter game "After the Fall," set in a post-apocalyptic, frozen Los Angeles overrun by mutated creatures.
-
C.
Lou
Lou is a common diminutive form of the given name Louise.
-
D.
Lee
Lee is a residential district in southeast London known for its suburban character, green spaces, and Victorian and Edwardian housing.
-
E.
Lee
Lee is a given name shared by numerous individuals across different cultures and professions.
- 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_69bd43f9efa081908314cb3e94fa1695 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6c99b46c8190b6fbcf9f98b9e993 |
completed | March 20, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be4dc02118819093f4dfad16c6085f |
completed | March 21, 2026, 7:50 a.m. |
Created at: March 20, 2026, 1:24 p.m.