Triple
T4135139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dasani |
E85134
|
entity |
| Predicate | usesWaterTreatment |
P54063
|
FINISHED |
| Object | purification |
—
|
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: purification | Statement: [Dasani, usesWaterTreatment, purification]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesWaterTreatment Context triple: [Dasani, usesWaterTreatment, purification]
-
A.
waterQualityUse
Indicates the way in which water quality is evaluated, classified, or applied for specific purposes or uses.
-
B.
isPartOfWaterSystem
Indicates that one entity is a component, segment, or subsystem within a larger water distribution, treatment, or management system.
-
C.
hasWaterManagementIssue
Indicates that an entity experiences problems or challenges related to the control, distribution, quality, or availability of water.
-
D.
waterType
Indicates the specific kind or category of water associated with an entity (e.g., fresh, salt, brackish).
-
E.
waterUse
Indicates the amount or manner in which water is consumed, utilized, or withdrawn by an entity or activity.
- 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_69aed935ccd881909dc61f81bcdb7a78 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af018a54848190987f18c066c75068 |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af039fb19c8190b20e62a3b3ad25c1 |
completed | March 9, 2026, 5:30 p.m. |
Created at: March 9, 2026, 3:43 p.m.