Triple
T14941480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Děčín |
E372539
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Halton |
E735978
|
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: Halton | Statement: [Děčín, twinTown, Halton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Halton Context triple: [Děčín, twinTown, Halton]
-
A.
Halton
Halton is a local government borough in Cheshire, England, encompassing the towns of Runcorn and Widnes along the River Mersey.
-
B.
Halton
Halton is a village and civil parish in Lancashire, England, situated near the River Lune and forming part of the wider Lune Valley area.
-
C.
Halton
chosen
Halton is a regional municipality in Ontario, Canada, encompassing several communities including the rapidly growing Town of Milton.
-
D.
Halton Hills
Halton Hills is a town in Ontario, Canada, known for its mix of rural landscapes, historic communities like Georgetown and Acton, and its location within the commuter belt of the Toronto region.
-
E.
Brampton
Brampton is a large suburban city in the Greater Toronto Area known for its diverse population and rapidly growing economy.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded68c1df0819084c0cd61b207d398 |
completed | April 15, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe7e929f3881908560b8428e72327d |
completed | May 9, 2026, 12:23 a.m. |
Created at: April 10, 2026, 2:38 a.m.