Triple
T22123316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rother |
E546726
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | 1066 Country |
—
|
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: 1066 Country | Statement: [Rother, contains, 1066 Country]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 1066 Country Context triple: [Rother, contains, 1066 Country]
-
A.
The Country
"The Country" is a short story by William Faulkner that explores life, class, and moral conflict in the rural American South.
-
B.
The Country
"The Country" is a novel by American writer Ken Baumann, known for its experimental style and introspective exploration of identity and place.
-
C.
The Country
"The Country" is a darkly comic stage play by British dramatist Martin Crimp that explores deception, power dynamics, and moral ambiguity within an ostensibly civilized middle-class couple.
-
D.
White Cliffs Country
chosen
White Cliffs Country is a coastal region in southeast England famed for its iconic white chalk cliffs, historic ports, and seaside landscapes.
-
E.
Black Country
The Black Country is an industrial region in the West Midlands of England historically known for coal mining, ironworking, and heavy manufacturing.
- 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_69e11e39bf348190b541bfa16a7b71e0 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1297f3fb48190b6aaca18b40c37ab |
completed | April 28, 2026, 9:41 p.m. |
Created at: April 16, 2026, 8:31 p.m.