Triple
T13929770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MOD Boscombe Down |
E334958
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Amesbury |
E212097
|
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: Amesbury | Statement: [MOD Boscombe Down, locatedNear, Amesbury]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amesbury Context triple: [MOD Boscombe Down, locatedNear, Amesbury]
-
A.
Amesbury
Amesbury is a historic New England city in northeastern Massachusetts known for its early shipbuilding and industrial heritage along the Merrimack River.
-
B.
Amesbury
chosen
Amesbury is a historic town in Wiltshire, England, best known for its proximity to the prehistoric monument of Stonehenge.
-
C.
Romsey
Romsey is a historic market town in Hampshire, England, known for its medieval abbey and riverside setting.
-
D.
Sherborne
Sherborne is a small rural village in West Oxfordshire, England, known for its traditional Cotswold stone buildings and picturesque countryside setting.
-
E.
Sherborne
Sherborne is a historic market town in southwest England renowned for its medieval abbey, castles, and well-preserved architecture.
- 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_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2aa900a0819095eeb1bc46b0336e |
completed | April 14, 2026, 11:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce8262288190a7e6dd647b1917c1 |
completed | May 3, 2026, 10:38 p.m. |
Created at: April 9, 2026, 10:16 p.m.