Triple
T12956892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scarlett Estevez |
E310034
|
entity |
| Predicate | characterIn |
P12208
|
FINISHED |
| Object | Lucifer |
E1013440
|
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: Lucifer | Statement: [Scarlett Estevez, characterIn, Lucifer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucifer Context triple: [Scarlett Estevez, characterIn, Lucifer]
-
A.
Lucifer
Lucifer is the fallen angel and ruler of Hell in Dante Alighieri’s Divine Comedy, embodying ultimate evil and the antithesis of divine order.
-
B.
Lucifer
Lucifer is the sly, spoiled pet cat of Lady Tremaine in Disney’s Cinderella, known for tormenting Cinderella and her animal friends.
-
C.
Lucifer
chosen
"Lucifer" is an American urban fantasy television series that follows Lucifer Morningstar, the Devil, as he abandons Hell to run a Los Angeles nightclub and consult for the LAPD.
-
D.
Lucifer Box
Lucifer Box is a flamboyant Edwardian-era British secret agent and portrait painter who stars as the witty, decadent protagonist of Mark Gatiss’s comic spy novels.
-
E.
Lucifer Falls
Lucifer Falls is a dramatic multi-tiered waterfall in New York’s Finger Lakes region, known for its steep gorge setting and scenic hiking trails.
- 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e2c5bf481908ca6adcfd3354f71 |
completed | April 10, 2026, 10:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c0f0b4c08190a6cb0a098ca6d67b |
completed | May 3, 2026, 3:28 a.m. |
Created at: April 9, 2026, 5:44 p.m.