Triple
T22896736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maurice Lucas |
E568193
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Lucas |
—
|
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: Lucas | Statement: [Maurice Lucas, familyName, Lucas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucas Context triple: [Maurice Lucas, familyName, Lucas]
-
A.
Lucas
chosen
Lucas is the surname of George Lucas, the influential American filmmaker best known as the creator of the Star Wars and Indiana Jones franchises.
-
B.
Lucas
Lucas is a prominent former player for the Ohio State Buckeyes men's basketball program, recognized as one of the team's standout athletes.
-
C.
Lucas
"Lucas" is a large-scale photorealistic portrait painting by American artist Chuck Close, exemplifying his meticulous, grid-based technique.
-
D.
Lucas
Lucas is a party involved in the landmark U.S. Supreme Court case Lucas v. Forty-Fourth General Assembly of Colorado, which addressed legislative apportionment and voting rights.
-
E.
Lucas
Lucas is a 1986 coming-of-age drama film best known for featuring one of Winona Ryder’s earliest prominent screen roles.
- 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_69e2458c23ec81908fa2570692c6614f |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1801358488190aa2a51f0943ea5bd |
completed | April 29, 2026, 3:50 a.m. |
Created at: April 17, 2026, 3:41 p.m.