Triple
T3808799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bleeding Kansas crisis |
E93078
|
entity |
| Predicate | hasMainConflict |
P5022
|
FINISHED |
| Object | pro-slavery forces vs. anti-slavery forces |
—
|
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: pro-slavery forces vs. anti-slavery forces | Statement: [Bleeding Kansas crisis, hasMainConflict, pro-slavery forces vs. anti-slavery forces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainConflict Context triple: [Bleeding Kansas crisis, hasMainConflict, pro-slavery forces vs. anti-slavery forces]
-
A.
mainConflict
chosen
Indicates the primary opposing force, problem, or struggle that drives tension and narrative progression between entities or sides.
-
B.
hasPartOfConflict
Indicates that one conflict includes another conflict as a constituent or subordinate part of it.
-
C.
hasOngoingConflict
Indicates that there is a current, unresolved state of opposition, dispute, or hostilities between the related entities.
-
D.
notableConflictWith
Indicates a significant, recognized conflict or dispute that exists or has existed between the related entities.
-
E.
hasIdeologicalConflict
Indicates a relationship where two entities hold opposing or incompatible ideologies that put them in conflict with each other.
- 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_69aed96a60088190ab1df8390fffc935 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7482d708190a3ec74745b102a4c |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:16 p.m.