Triple
T26194567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banpo Bridge Rainbow Fountain |
E655061
|
entity |
| Predicate | hasNozzlesOn |
P192205
|
FINISHED |
| Object | both sides of Banpo Bridge |
—
|
LITERAL 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: both sides of Banpo Bridge | Statement: [Banpo Bridge Rainbow Fountain, hasNozzlesOn, both sides of Banpo Bridge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNozzlesOn Context triple: [Banpo Bridge Rainbow Fountain, hasNozzlesOn, both sides of Banpo Bridge]
-
A.
numberOfNozzles
Indicates the quantity of nozzles associated with or present on a given entity.
-
B.
nozzleType
Indicates the specific kind or category of nozzle associated with or used by an entity.
-
C.
hasFillingSystem
Indicates that an entity is equipped with or uses a particular filling system or mechanism.
-
D.
doesNotHaveOutletTo
Indicates that one entity lacks any direct outlet, passage, or connection leading to another entity or to an external space.
-
E.
nozzleDiameter
Indicates the size of the opening of a nozzle, typically measured as the diameter of its exit orifice.
- F. None of above. chosen
Provenance (4 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_69ee5b48236c81908fe385b6afc4f60b |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69fd02680d948190a3463fb119ba8556 |
completed | May 7, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69fcf89c69b4819082bbc564bd15137d |
completed | May 7, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69fd026757a081909911a59a78652709 |
completed | May 7, 2026, 9:21 p.m. |
Created at: April 26, 2026, 8:45 p.m.