Triple
T28970343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blair Mountain, West Virginia |
E734252
|
entity |
| Predicate | conflictScale |
P169661
|
FINISHED |
| Object | one of the largest armed uprisings in U.S. labor history |
—
|
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: one of the largest armed uprisings in U.S. labor history | Statement: [Blair Mountain, West Virginia, conflictScale, one of the largest armed uprisings in U.S. labor history]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conflictScale Context triple: [Blair Mountain, West Virginia, conflictScale, one of the largest armed uprisings in U.S. labor history]
-
A.
conflictType
Indicates the specific kind or category of conflict that characterizes the relationship or interaction between entities.
-
B.
conflictIn
Indicates that one entity is involved in, associated with, or occurs within a particular conflict or dispute.
-
C.
conflictGround
Indicates that one entity is the cause, basis, or subject matter of a conflict involving another entity.
-
D.
armedConflictLevel
Indicates the intensity or severity of ongoing or potential armed conflict between parties.
-
E.
settingOfConflict
Indicates the location or context in which a conflict between entities takes place.
- 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_69f05b0d1e7c819092baab93d3fe277e |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f68048391c8190abe6580678f8a9ef |
completed | May 2, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69f67e40af9881908de3a4aa15f70a83 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f67f7e116c819099aec724e9ef3763 |
completed | May 2, 2026, 10:49 p.m. |
Created at: April 28, 2026, 9:05 a.m.