Triple
T15914577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Jeter |
E385935
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Open Range |
E109412
|
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: Open Range | Statement: [Michael Jeter, notableWork, Open Range]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Open Range Context triple: [Michael Jeter, notableWork, Open Range]
-
A.
Open Range
chosen
Open Range is a 2003 Western film directed by and starring Kevin Costner, known for its classic frontier setting, strong character-driven storytelling, and realistic depictions of gunfights.
-
B.
Ranchland
Ranchland is a small rural community in southern Alberta, Canada, known for its agricultural and ranching landscape within the Municipal District of Willow Creek No. 26.
-
C.
Landman
Landman is a surname of English origin, sometimes appearing as a variant spelling of "Lanman."
-
D.
Red Country
Red Country is a gritty fantasy novel by British author Joe Abercrombie, set in his First Law world and blending Western-style themes with dark, character-driven adventure.
-
E.
The Range
The Range is a rural locality in South Australia known for its scenic hills, vineyards, and agricultural landscapes.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1566216d481908dd6e3acaa26fd45 |
completed | April 16, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb0592b5c8190a4597644864a6bcb |
completed | May 9, 2026, 10:08 p.m. |
Created at: April 10, 2026, 4:52 a.m.