Triple
T7597486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Borough of Pendle |
E179893
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Barley |
E387886
|
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: Barley | Statement: [Borough of Pendle, contains, Barley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barley Context triple: [Borough of Pendle, contains, Barley]
-
A.
Barley
chosen
Barley is a small rural village in the North Hertfordshire district of England, known for its historic buildings and traditional English countryside setting.
-
B.
Emmer
Emmer is a river in northwestern Germany that flows through Lower Saxony and North Rhine-Westphalia before joining the Weser.
-
C.
Millet
Millet is a common French surname borne by several notable figures, including artists and sculptors.
-
D.
Triticum aestivum
Triticum aestivum is the common bread wheat, a major cereal crop globally cultivated for its grain used in flour and numerous food products.
-
E.
Dinkel
Dinkel is a small river in the eastern Netherlands and western Germany, known for flowing through the Twente region and its relatively unspoiled natural 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_69c69f3487ec8190bf7acdf2dd91e6d6 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f9d4d3408190b9650347c7850c47 |
completed | March 27, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c861a7a7088190ba8d72e63f4dcaa0 |
completed | March 28, 2026, 11:17 p.m. |
Created at: March 27, 2026, 3:53 p.m.