Triple
T1154893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Washington |
E23759
|
entity |
| Predicate | waterQualityImprovedAfter |
P25366
|
FINISHED |
| Object | sewage diversion projects in the 1960s |
—
|
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: sewage diversion projects in the 1960s | Statement: [Lake Washington, waterQualityImprovedAfter, sewage diversion projects in the 1960s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterQualityImprovedAfter Context triple: [Lake Washington, waterQualityImprovedAfter, sewage diversion projects in the 1960s]
-
A.
waterQualityUse
Indicates the way in which water quality is evaluated, classified, or applied for specific purposes or uses.
-
B.
hasWaterQualityHistory
Indicates that an entity is associated with a record or series of records describing changes or measurements of its water quality over time.
-
C.
hasWaterClarity
Indicates the degree to which water in a given context is clear, transparent, or free from visible impurities.
-
D.
waterType
Indicates the specific kind or category of water associated with an entity (e.g., fresh, salt, brackish).
-
E.
sourceOfWaterSupply
Indicates that one entity serves as the origin or provider of another entity’s water supply.
- 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_69a493f0d32c8190ac74bad3c87f2641 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bc8fbb548190865b1bf019f2bde4 |
completed | March 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69a4bb50d19c81908a98dbbb04a8906f |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bc47fce48190825d3a877251f789 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:44 p.m.