Triple
T509820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flint, Michigan |
E10580
|
entity |
| Predicate | publicHealthIssue |
P4720
|
FINISHED |
| Object | lead contamination in drinking 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: lead contamination in drinking water | Statement: [Flint, Michigan, publicHealthIssue, lead contamination in drinking water]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publicHealthIssue Context triple: [Flint, Michigan, publicHealthIssue, lead contamination in drinking water]
-
A.
hasHealthConcern
chosen
Indicates that an entity has a specific health-related issue, condition, or concern associated with it.
-
B.
underlyingIssue
Indicates that one situation, problem, or condition is the fundamental cause or root problem behind another.
-
C.
diseaseType
Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
-
D.
positionOnHealthCare
Indicates a person or entity’s stance, opinion, or policy preference regarding health care systems, services, or reforms.
-
E.
healthProxy
Indicates that one entity is authorized to make health-related or medical decisions on behalf of another entity.
- 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.