Triple
T11290728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mid Suffolk |
E267315
|
entity |
| Predicate | hasVillage |
P4011
|
FINISHED |
| Object | Laxfield |
E332903
|
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: Laxfield | Statement: [Mid Suffolk, hasVillage, Laxfield]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laxfield Context triple: [Mid Suffolk, hasVillage, Laxfield]
-
A.
Laxfield
chosen
Laxfield is a historic rural village and civil parish in the English county of Suffolk, known for its traditional architecture and agricultural surroundings.
-
B.
Darfield
Darfield is a village in South Yorkshire, England, historically associated with coal mining and situated near the River Dearne.
-
C.
Baverstock
Baverstock is a small rural hamlet in Wiltshire, England, known for its historic church and tranquil countryside setting.
-
D.
Sandisfield
Sandisfield is a small rural town in southwestern Massachusetts known for its forests, reservoirs, and quiet, sparsely populated landscape.
-
E.
Battisford
Battisford is a small rural village and civil parish located in the English county of Suffolk.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e989fdac81909a4a75f1f68b55c6 |
completed | April 9, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4f49badc88190a3195e919900f0c3 |
completed | April 19, 2026, 3:28 p.m. |
Created at: April 8, 2026, 9:32 p.m.