Triple
T3875432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aberdeen railway station |
E92488
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Inverness |
E50911
|
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: Inverness | Statement: [Aberdeen railway station, connectsTo, Inverness]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Inverness Context triple: [Aberdeen railway station, connectsTo, Inverness]
-
A.
Inverness
chosen
Inverness is a city in the Scottish Highlands that serves as a major cultural and administrative center for the region.
-
B.
Nairn
Nairn is a coastal town in the Highland council area of Scotland, known as a seaside resort on the Moray Firth.
-
C.
Greenock
Greenock is a historic port town and former shipbuilding center on the River Clyde in western Scotland.
-
D.
Balerno
Balerno is a suburban village on the outskirts of Edinburgh, Scotland, known for its scenic setting near the Pentland Hills and its residential character.
-
E.
Aberdeen
Aberdeen is a small rural town in the Upper Hunter region of New South Wales, Australia, known historically for its agricultural and meat-processing industries.
- 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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec706434819095e0d2b376adb548 |
completed | March 9, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b55612ab7081909ab9375da1e4119b |
completed | March 14, 2026, 12:35 p.m. |
Created at: March 9, 2026, 3:20 p.m.