Triple
T14040431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Batten |
E337830
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Turnchapel |
E1068902
|
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: Turnchapel | Statement: [Mount Batten, adjacentTo, Turnchapel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Turnchapel Context triple: [Mount Batten, adjacentTo, Turnchapel]
-
A.
Turnchapel
chosen
Turnchapel is a small coastal village and former naval fuel depot area located on the southern edge of Plymouth, England.
-
B.
Harrowgate
Harrowgate is a neighborhood in North Philadelphia, Pennsylvania, known for its historic roots as an early industrial and residential area.
-
C.
Ingatestone
Ingatestone is a historic village and civil parish in southeast England known for its traditional architecture and commuter links to London.
-
D.
Oakengates
Oakengates is a small town in Shropshire, England, now effectively part of the Telford urban area.
-
E.
Shadoxhurst
Shadoxhurst is a rural village and civil parish in the Ashford district of Kent, England, known for its woodland surroundings and traditional English countryside character.
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de311814e48190adb637e1c97c0658 |
completed | April 14, 2026, 12:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc33dbc8c819080b6cb3d589da7a1 |
completed | May 6, 2026, 10:39 p.m. |
Created at: April 9, 2026, 10:20 p.m.