Triple
T8974096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quatre Bras |
E214340
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Waterloo |
E678545
|
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: [Quatre Bras, locatedNear, Waterloo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waterloo Context triple: [Quatre Bras, locatedNear, Waterloo]
-
A.
Waterloo
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
chosen
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 a mid-sized Canadian city in southwestern Ontario known for its universities, tech industry, and role within the Kitchener–Waterloo metropolitan area.
- 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_69ca839dbf608190a2f5990477115d29 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6783abe48190840e652fc2acf28f |
completed | April 1, 2026, 12:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc966f7d881908f4f80c2a0d820fe |
completed | April 3, 2026, 2:06 p.m. |
Created at: March 30, 2026, 7:02 p.m.