Triple
T22986310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jordan and Syria |
E571615
|
entity |
| Predicate | waterIssueType |
P26834
|
FINISHED |
| Object | allocation of surface water |
—
|
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: allocation of surface water | Statement: [Jordan and Syria, waterIssueType, allocation of surface water]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterIssueType Context triple: [Jordan and Syria, waterIssueType, allocation of surface water]
-
A.
waterQualityIssues
Indicates that there are problems or concerns with the condition, safety, or suitability of a water source.
-
B.
waterType
Indicates the specific kind or category of water associated with an entity (e.g., fresh, salt, brackish).
-
C.
hasWaterManagementIssue
chosen
Indicates that an entity experiences problems or challenges related to the control, distribution, quality, or availability of water.
-
D.
waterServiceType
Indicates the specific kind or category of water service provided or associated with an entity.
-
E.
waterInfrastructure
Indicates the existence, development, or management of systems and facilities that supply, store, treat, or distribute water between entities.
- F. None of above.
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_69e245b3c50481908bb3741ec9f40862 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182996ee08190ab74014ee7ecac2b |
completed | April 29, 2026, 4:01 a.m. |
| PD | Predicate disambiguation | batch_69ef3b974e7c8190b8be11dbb4518693 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:49 p.m.