Triple
T5554556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tenterden |
E145605
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Ashford |
E46676
|
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: Ashford | Statement: [Tenterden, locatedNear, Ashford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ashford Context triple: [Tenterden, locatedNear, Ashford]
-
A.
Ashford
chosen
Ashford is a large and rapidly growing town in the county of Kent in southeast England, known as a key transport hub with high-speed rail links to London and continental Europe.
-
B.
Ashford
Ashford is a small rural town in northern New South Wales, Australia, known for agriculture and its proximity to natural attractions such as caves and rivers.
-
C.
ASHFORD
ASHFORD is a town in the borough of Spelthorne in Surrey, England, forming part of the London commuter belt.
-
D.
New Ashford
New Ashford is a small rural town in western Massachusetts, United States, known for its scenic setting in the Berkshires.
-
E.
Bedford
Bedford is a historic market town and the county town of Bedfordshire in eastern England, situated on the River Great Ouse.
- 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_69c008fcaf788190bafa02a1917ee73b |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01ffaf4fc8190bf27014d21954a70 |
completed | March 22, 2026, 4:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0283878d88190ac60064e604aa002 |
completed | March 22, 2026, 5:34 p.m. |
Created at: March 22, 2026, 3:36 p.m.