Triple
T31970577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bloody Creek |
E816300
|
entity |
| Predicate | conflictParticipants |
P167916
|
FINISHED |
| Object | British forces |
—
|
NE NERFINISHED |
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: British forces | Statement: [Bloody Creek, conflictParticipants, British forces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conflictParticipants Context triple: [Bloody Creek, conflictParticipants, British forces]
-
A.
conflictParticipantIn
chosen
Indicates that an entity takes part as a participant in a specific conflict or dispute.
-
B.
partnerInConflictWith
Indicates that two entities are engaged as opposing partners or sides within the same conflict or dispute.
-
C.
conflictsInvolvedIn
Indicates that an entity participates as a party or actor in one or more conflicts.
-
D.
coalitionParticipants
Indicates that certain entities are members or participants in the same coalition.
-
E.
opposingParticipants
Indicates that the related entities are participants positioned in opposition to each other within the same interaction, event, or context.
- 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_69f348f5ae5481909da0247869f51955 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 12:10 a.m.