Triple
T11695467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Llangollen Canal |
E277982
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Chirk |
E153586
|
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: Chirk | Statement: [Llangollen Canal, passesThrough, Chirk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chirk Context triple: [Llangollen Canal, passesThrough, Chirk]
-
A.
Chirk
chosen
Chirk is a small Welsh border town known for its historic castle and aqueduct near the England–Wales boundary.
-
B.
Chirton
Chirton is a residential area and former village within the metropolitan borough of North Tyneside in North East England.
-
C.
Tyrlaching
Tyrlaching is a small rural municipality in southeastern Bavaria, Germany, known for its agricultural character and location within the district of Altötting.
-
D.
Torphichen
Torphichen is a historic village in central Scotland known for its medieval preceptory of the Knights Hospitaller and its picturesque rural setting.
-
E.
Sherkston
Sherkston is a lakeside community in Ontario, Canada, known for its beaches, campgrounds, and recreational resort atmosphere along Lake Erie.
- 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_69d6aafe02d881909900d54ad7d4af84 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a47cef60819088b7cc3a3a711e4c |
completed | April 10, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef1471cba88190a7abdcbf4f579ea9 |
completed | April 27, 2026, 7:46 a.m. |
Created at: April 8, 2026, 9:40 p.m.