Triple
T9520595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keith Powell |
E229632
|
entity |
| Predicate | appearedIn |
P795
|
FINISHED |
| Object | Lucifer |
E780290
|
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: [Keith Powell, appearedIn, Lucifer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucifer Context triple: [Keith Powell, appearedIn, 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 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.
-
C.
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.
-
D.
Lucifer Morningstar
Lucifer Morningstar is a central character in the TV series "The Sandman," depicted as a powerful and androgynous ruler of Hell portrayed by Gwendoline Christie.
-
E.
Lucifer (TV series)
chosen
Lucifer is an American fantasy crime drama television series that follows the Devil as he abandons Hell to run a nightclub in Los Angeles and consult for the LAPD.
- 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_69ca847870a881909d8d751a7d29da39 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9883c5c48190a6583921afe9730a |
completed | April 1, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d13a56da2481909873c8d567b3fd5f |
completed | April 4, 2026, 4:20 p.m. |
Created at: March 30, 2026, 7:59 p.m.