Triple
T18131675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jessica Lucas |
E434027
|
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: [Jessica Lucas, familyName, Lucas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucas Context triple: [Jessica 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 1986 coming-of-age drama film best known for featuring one of Winona Ryder’s earliest prominent screen roles.
-
C.
Lucas
Lucas is the Latin form of the name Luke, traditionally associated with St. Luke the Evangelist in Christian tradition.
-
D.
Lucas
Lucas is a place situated east of Allen, likely a town or city in the same general region.
-
E.
Lucas
"Lucas" is a large-scale photorealistic portrait painting by American artist Chuck Close, exemplifying his meticulous, grid-based technique.
- 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddf2c68881909dfbe59df15ddccc |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 10:29 a.m.