Triple
T12924101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Base 31 |
E309198
|
entity |
| Predicate | conflictDomain |
P3680
|
FINISHED |
| Object | space |
—
|
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: space | Statement: [Base 31, conflictDomain, space]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conflictDomain Context triple: [Base 31, conflictDomain, space]
-
A.
conflictRegion
Indicates that the entities are located in or associated with a geographic area characterized by active or recent conflict, tension, or hostilities.
-
B.
conflictSpecific
Indicates a specific, concrete instance or type of conflict that exists between the related entities.
-
C.
conflictSource
Indicates that one entity is the origin, cause, or initiating side of a conflict involving another entity.
-
D.
conflictType
Indicates the specific kind or category of conflict that characterizes the relationship or interaction between entities.
-
E.
conflictContext
chosen
Indicates the situational background or circumstances within which a conflict between entities occurs or is interpreted.
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971e9576c81908eb59569af6da877 |
completed | April 10, 2026, 9:55 p.m. |
| PD | Predicate disambiguation | batch_69d96fa9b7708190a9e9fa30f59ff580 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:42 p.m.