Triple
T18440515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warren Ellis |
E450513
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Fell |
—
|
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: Fell | Statement: [Warren Ellis, notableWork, Fell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fell Context triple: [Warren Ellis, notableWork, Fell]
-
A.
Fell
chosen
Fell is a noir-inspired horror comic book series written by Warren Ellis and illustrated by Ben Templesmith, known for its grim, self-contained crime stories set in the decaying city of Snowtown.
-
B.
Fell
Fell is a surname of English and Scandinavian origin borne by various notable individuals across politics, arts, and other fields.
-
C.
Wind Fell
Wind Fell is a hill in the Ettrick Hills range of the Southern Uplands in Scotland, known for its open moorland and upland walking routes.
-
D.
Rock Fall
Rock Fall was a talented American Thoroughbred racehorse known for his impressive sprinting ability and graded stakes victories before his career was tragically cut short.
-
E.
The Falling
The Falling is a 2014 British drama film set in a girls' school in the 1960s, exploring mass hysteria and adolescent sexuality, in which Monica Dolan plays a key role.
- 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_69d8d381d6388190a9e94e9c658174e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51c10a86c819091196968b648fc92 |
completed | April 19, 2026, 6:16 p.m. |
Created at: April 10, 2026, 11:30 a.m.