Triple
T2857837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flint water crisis |
E63245
|
entity |
| Predicate | mainPollutant |
P29039
|
FINISHED |
| Object | lead |
—
|
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 | Statement: [Flint water crisis, mainPollutant, lead]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainPollutant Context triple: [Flint water crisis, mainPollutant, lead]
-
A.
targetPollutant
chosen
Indicates that something is the specific pollutant that is being aimed at, affected, or addressed by an action, process, or regulation.
-
B.
pollutantsCovered
Indicates that certain pollutants are included within the scope, protection, regulation, or consideration defined by a particular entity, policy, or agreement.
-
C.
wasHeavilyPollutedDuring
Indicates that a place or environment experienced a high level of pollution during a specified time period.
-
D.
historicallyPollutedBy
Indicates that an entity has experienced pollution in the past as a result of actions or emissions from another entity.
-
E.
hasEnvironmentalImpactOn
Indicates that one entity affects or alters the environmental conditions, quality, or ecological state 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_69ab4c41e8c08190a9e8f5249cc12610 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf89d3b4819086936f26d8683a2a |
completed | March 7, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69abdd10aef88190b750aae07e7df4dc |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:02 p.m.