Triple
T36249651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Devil Mine |
E891761
|
entity |
| Predicate | remediationActivity |
P184809
|
FINISHED |
| Object | site investigation |
—
|
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: site investigation | Statement: [Red Devil Mine, remediationActivity, site investigation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: remediationActivity Context triple: [Red Devil Mine, remediationActivity, site investigation]
-
A.
remedy
Indicates that one entity serves to cure, alleviate, or counteract a problem, illness, or undesirable condition affecting another entity.
-
B.
hasRemediationStatus
Indicates the current state or progress of remediation efforts applied to an identified issue, risk, or non-compliance.
-
C.
educationalActivity
Indicates an action or relationship in which one entity engages in or provides a learning or teaching activity for another.
-
D.
builtAsMitigationFor
Indicates that one entity was constructed specifically to reduce, prevent, or counteract a particular risk, problem, or adverse impact associated with another entity.
-
E.
managedAct
Indicates that one entity oversaw, directed, or was responsible for carrying out a particular action or activity.
- 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_69f76e4599108190811532e707d6bc2c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b5f89c5c8190825ed5d4317c540c |
completed | May 3, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c44390819084fb5558b354658f |
completed | May 3, 2026, 8:49 p.m. |
| PDg | Predicate description generation | batch_69f7b57aa0848190a22c31c3ff90e0ab |
completed | May 3, 2026, 8:52 p.m. |
Created at: May 3, 2026, 4:09 p.m.