Triple
T3386016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyde Park |
E71303
|
entity |
| Predicate | hasBodyOfWater |
P1778
|
FINISHED |
| Object | the Long Water |
E328295
|
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: the Long Water | Statement: [Hyde Park, hasBodyOfWater, the Long Water]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: the Long Water Context triple: [Hyde Park, hasBodyOfWater, the Long Water]
-
A.
The Long Water
chosen
The Long Water is a picturesque ornamental lake in London's Kensington Gardens, forming the western half of the Serpentine.
-
B.
Lunan Water
Lunan Water is a river in Angus, Scotland, that flows into the North Sea at the scenic Lunan Bay.
-
C.
West Water
West Water is a tributary stream of the North Esk River in eastern Scotland.
-
D.
Hermitage Water
Hermitage Water is a river in the Scottish Borders that flows past the historic Hermitage Castle and through a remote, rural valley.
-
E.
Sylvan Water
Sylvan Water is a picturesque pond within Brooklyn’s historic Green-Wood Cemetery, known for its tranquil scenery and surrounding monuments.
- 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_69ad85a8fd9c819095ecedf838d2bf1b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb662d190819085b211dac85a83b2 |
completed | March 8, 2026, 5:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b33455ae2481908e6478cb240b31c1 |
completed | March 12, 2026, 9:47 p.m. |
Created at: March 8, 2026, 3:14 p.m.