Triple
T761058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marine Corps Base Camp Lejeune |
E16068
|
entity |
| Predicate | contaminant |
P8036
|
FINISHED |
| Object | trichloroethylene |
—
|
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: trichloroethylene | Statement: [Marine Corps Base Camp Lejeune, contaminant, trichloroethylene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contaminant Context triple: [Marine Corps Base Camp Lejeune, contaminant, trichloroethylene]
-
A.
toxinType
chosen
Indicates the specific kind or category of toxin associated with an entity.
-
B.
toxicTo
Indicates that one entity causes harm, poisoning, or adverse effects to another when exposed or applied.
-
C.
hasEnvironmentalImpactOn
Indicates that one entity affects or alters the environmental conditions, quality, or ecological state of another entity.
-
D.
environmentalRemediation
Indicates actions or processes undertaken to remove, reduce, or neutralize pollution or environmental damage in order to restore a site or ecosystem to a safer or more natural condition.
-
E.
condemnation
Indicates that an entity expresses strong disapproval or denunciation of another entity, action, or situation.
- 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_69a493684ee48190bd43b7c78da4aec8 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a682e7d081909c9cd7839a49fb0b |
completed | March 1, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69a4a5048a8081908d0542214142664a |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.