Triple
T28500348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dayan Old Town |
E721213
|
entity |
| Predicate | hasTraditionalWaterSystem |
P194119
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Dayan Old Town, hasTraditionalWaterSystem, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalWaterSystem Context triple: [Dayan Old Town, hasTraditionalWaterSystem, yes]
-
A.
isPartOfWaterSystem
Indicates that one entity is a component, segment, or subsystem within a larger water distribution, treatment, or management system.
-
B.
hasWaterServiceFrom
Indicates that one entity receives its water supply or water-related services from another entity.
-
C.
hasWaterAvailability
Indicates that an entity has access to or is supplied with a certain amount or level of water.
-
D.
hasWaterManagementStructure
Indicates that one entity possesses, contains, or is associated with a built feature used to control, store, convey, or manage water.
-
E.
hasWaterUse
Indicates a relationship where one entity utilizes or consumes water for a particular purpose, process, or function.
- 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_69f01a5afdac8190ac6e72d5c100bd58 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69fd64bc86848190a49f451a8fc5cf1e |
completed | May 8, 2026, 4:21 a.m. |
| PD | Predicate disambiguation | batch_69fd5ff4a648819090756d90fd195d9a |
completed | May 8, 2026, 4 a.m. |
| PDg | Predicate description generation | batch_69fd64bb345c819096a35c72784a8ce3 |
completed | May 8, 2026, 4:21 a.m. |
Created at: April 28, 2026, 3:06 a.m.