Triple
T2108726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brega |
E42453
|
entity |
| Predicate | conflictTypeAtLocation |
P18893
|
FINISHED |
| Object | urban warfare during 2011 Libyan Civil War |
—
|
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: urban warfare during 2011 Libyan Civil War | Statement: [Brega, conflictTypeAtLocation, urban warfare during 2011 Libyan Civil War]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conflictTypeAtLocation Context triple: [Brega, conflictTypeAtLocation, urban warfare during 2011 Libyan Civil War]
-
A.
conflictType
Indicates the specific kind or category of conflict that characterizes the relationship or interaction between entities.
-
B.
conflictContext
Indicates the situational background or circumstances within which a conflict between entities occurs or is interpreted.
-
C.
conflictSpecific
chosen
Indicates a specific, concrete instance or type of conflict that exists between the related entities.
-
D.
conflictResult
Indicates the outcome or consequence that arises from a particular conflict between entities.
-
E.
numberOfConflicts
Indicates the count of distinct conflicts associated with or involving a given entity 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_69a8871040f08190aac2e2d0ab6b47ad |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbae03f308190841f5a419bb821f6 |
completed | March 7, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69abb7b7b6288190afa11b4d93bd5666 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.