Triple
T509819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flint, Michigan |
E10580
|
entity |
| Predicate | waterSourceHistory |
P4102
|
FINISHED |
| Object | switched to Flint River in 2014 |
—
|
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: switched to Flint River in 2014 | Statement: [Flint, Michigan, waterSourceHistory, switched to Flint River in 2014]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterSourceHistory Context triple: [Flint, Michigan, waterSourceHistory, switched to Flint River in 2014]
-
A.
waterSource
chosen
Indicates that one entity serves as the source or provider of water for another entity.
-
B.
waterOrigin
Indicates the source or starting location from which the water originates or is supplied.
-
C.
waterSourceType
Indicates the kind or category of source from which water is obtained.
-
D.
hasWaterQualityHistory
Indicates that an entity is associated with a record or series of records describing changes or measurements of its water quality over time.
-
E.
sourceOfWaterSupply
Indicates that one entity serves as the origin or provider of another entity’s water supply.
- 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_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f164a9d48190b525a97b5c06ffe2 |
completed | Feb. 28, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69a2edfe236481909901cc7d4281b33c |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.