Triple
T14970997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bedford Park |
E373316
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Darlington |
E245663
|
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: Darlington | Statement: [Bedford Park, adjacentTo, Darlington]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Darlington Context triple: [Bedford Park, adjacentTo, Darlington]
-
A.
Darlington
Darlington is a civil parish in New South Wales, Australia, that includes the locality of Darlington Point.
-
B.
Darlington
Darlington is a surname of English origin borne by various notable individuals across fields such as engineering, science, and public life.
-
C.
Darlington
Darlington is a market town and borough in County Durham, England, historically known for its pioneering role in railway development.
-
D.
Darlington
chosen
Darlington is a residential neighborhood in the city of Pawtucket, known as one of the oldest and most densely populated areas in Rhode Island.
-
E.
Darlington
Darlington is a rural locality in Queensland, Australia, known for its scenic landscapes and proximity to the mountainous Scenic Rim region.
- 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6e59a7c8190a1634a706ea68fda |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8be6ce68819099f841d83c6ca33d |
completed | May 9, 2026, 1:20 a.m. |
Created at: April 10, 2026, 2:49 a.m.