Triple
T11284916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A859 road |
E267160
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Leverburgh |
E501392
|
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: Leverburgh | Statement: [A859 road, connects, Leverburgh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leverburgh Context triple: [A859 road, connects, Leverburgh]
-
A.
Leverburgh
chosen
Leverburgh is a small coastal village on the Isle of Harris in Scotland’s Outer Hebrides, known as a ferry port and fishing community.
-
B.
Elizabethport
Elizabethport is a historic waterfront neighborhood and port district in the city of Elizabeth, New Jersey.
-
C.
Milport
Milport is a fictional British parliamentary constituency featured in Patrick O’Brian’s Aubrey–Maturin historical naval novels.
-
D.
Sandhaven
Sandhaven is a small coastal village in the Buchan area of Aberdeenshire, northeast Scotland, historically associated with fishing and maritime activity.
-
E.
Leamouth
Leamouth is a riverside district in East London where the River Lea meets the River Thames, known for its former industrial docks and recent waterside redevelopment.
- 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9855e8881909bd301718cbd8ca1 |
completed | April 9, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4f48070ac8190b0e4d49f42ac3896 |
completed | April 19, 2026, 3:28 p.m. |
Created at: April 8, 2026, 9:31 p.m.