Triple
T16202612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wellington Museum |
E393240
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Waterloo |
E265743
|
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: Waterloo | Statement: [Wellington Museum, locatedIn, Waterloo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waterloo Context triple: [Wellington Museum, locatedIn, Waterloo]
-
A.
Waterloo
chosen
Waterloo is a major district in central London known for its busy railway station, cultural venues like the Southbank Centre, and proximity to landmarks such as the London Eye and the River Thames.
-
B.
Waterloo
Waterloo was the original name of the settlement that later became the city of Austin, the capital of Texas.
-
C.
Waterloo
Waterloo is a village in North Lanarkshire, Scotland, forming part of the wider Wishaw area.
-
D.
Waterloo
Waterloo is a small village in eastern Nebraska, United States, located along the Elkhorn River just west of Omaha.
-
E.
Waterloo
Waterloo is an inner-city suburb of Sydney, Australia, known for its mix of public housing, industrial heritage, and rapid urban 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_69d87f1f5bd08190bd01cac0d5b9d2ef |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2270b84408190bfbf68f32bfc5b1a |
completed | April 17, 2026, 12:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffff130bcc8190a965d90e123d2dd9 |
completed | May 10, 2026, 3:44 a.m. |
Created at: April 10, 2026, 5:03 a.m.