Triple
T15118589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lewis Carroll |
E361105
|
entity |
| Predicate | bornIn |
P1
|
FINISHED |
| Object | Daresbury |
E361105
|
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: Daresbury | Statement: [Lewis Carroll, bornIn, Daresbury]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daresbury Context triple: [Lewis Carroll, bornIn, Daresbury]
-
A.
Daresbury
chosen
Daresbury is a village in Cheshire, England, best known as the birthplace of author Lewis Carroll and for its nearby national science and technology facilities.
-
B.
Daresbury, Cheshire, England
Daresbury, Cheshire, England is a small village best known as the birthplace of author and mathematician Lewis Carroll.
-
C.
Eddisbury
Eddisbury is a UK parliamentary constituency in Cheshire, England, represented in the House of Commons.
-
D.
Wilmslow
Wilmslow is an affluent town in Cheshire, England, known for its prosperous residential areas and location within the Greater Manchester commuter belt.
-
E.
Chorleywood
Chorleywood is a commuter village in South East England, known for its green spaces and location on the Metropolitan line within the London commuter belt.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0059e036c8190959ff3bde8f2356f |
completed | April 15, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69febfe3fe0081909d9d3a293373254b |
completed | May 9, 2026, 5:02 a.m. |
Created at: April 10, 2026, 3:06 a.m.