Triple
T7326684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Essex Police |
E168893
|
entity |
| Predicate | operatesIn |
P82
|
FINISHED |
| Object | Tendring |
E290177
|
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: Tendring | Statement: [Essex Police, operatesIn, Tendring]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tendring Context triple: [Essex Police, operatesIn, Tendring]
-
A.
Tendring district
chosen
Tendring district is a local government district in Essex, England, known for its coastal towns and seaside resorts including Clacton-on-Sea.
-
B.
Caistor
Caistor is a small historic market town in Lincolnshire, England, known for its Roman origins and Georgian architecture.
-
C.
Dereham
Dereham is a market town in the English county of Norfolk, known historically for its agriculture and rural character.
-
D.
Wivenhoe
Wivenhoe is a riverside town in Essex, England, known for its historic maritime character, artistic community, and proximity to the University of Essex.
-
E.
Thorpeness
Thorpeness is a quirky seaside village on the Suffolk coast of England, known for its mock-Tudor holiday homes, boating Meare, and the iconic House in the Clouds.
- 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_69c68a54cacc81908e3b773441f19566 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0a612c08190b7a3fefa811bbcec |
completed | March 27, 2026, 9:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7fa7f71888190a5025355c303c41d |
completed | March 28, 2026, 3:57 p.m. |
Created at: March 27, 2026, 3:03 p.m.