Triple
T6479327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Lark |
E146148
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Mildenhall |
E299688
|
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: Mildenhall | Statement: [River Lark, passesThrough, Mildenhall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mildenhall Context triple: [River Lark, passesThrough, Mildenhall]
-
A.
Mildenhall
chosen
Mildenhall is a market town in Suffolk, England, known for its historic parish church and proximity to RAF Mildenhall, a major Royal Air Force and United States Air Force base.
-
B.
Romsey
Romsey is a historic market town in Hampshire, England, known for its medieval abbey and riverside setting.
-
C.
Hoxne
Hoxne is a historic village in Suffolk, England, best known as the site where the famous late Roman Hoxne Hoard was discovered.
-
D.
Bettany
Bettany is an English surname most notably associated with actor Paul Bettany.
-
E.
Thanet
Thanet is a district on the eastern tip of Kent in southeast England, known for its coastal towns, maritime heritage, and seaside tourism.
- 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_69c008fec7408190af7b146dc63d9750 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a4e764c819086828bb841f588e0 |
completed | March 22, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c653aceb8c8190aff0abf15b049737 |
completed | March 27, 2026, 9:53 a.m. |
Created at: March 22, 2026, 4:51 p.m.