Triple
T30970607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winter War Museum in Suomussalmi |
E789085
|
entity |
| Predicate | focusesOnBelligerent |
P10155
|
FINISHED |
| Object | Finland |
—
|
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: Finland | Statement: [Winter War Museum in Suomussalmi, focusesOnBelligerent, Finland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusesOnBelligerent Context triple: [Winter War Museum in Suomussalmi, focusesOnBelligerent, Finland]
-
A.
belligerentFor
Indicates a relationship in which one entity is engaged in hostile or aggressive behavior toward, or in conflict with, another entity.
-
B.
belligerentAgainst
Indicates a hostile or aggressive stance, conflict, or antagonistic behavior directed by one entity against another.
-
C.
belligerentInterest
Indicates that an entity has a hostile, aggressive, or conflict-seeking attitude or stake toward another entity or situation.
-
D.
conflictBelligerent
chosen
Indicates that an entity is a participating belligerent (e.g., a country, group, or force) in a specific conflict.
-
E.
belligerentObjective
Indicates that an entity is the target or objective of hostile or warlike actions by another entity.
- 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_69f224c3a6b48190951add9b7b7f0271 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f78fd5a6388190bfda4bbb2e222e5b |
completed | May 3, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_69f78e2ac3fc819081a45c6841375c8d |
completed | May 3, 2026, 6:04 p.m. |
Created at: April 29, 2026, 8:54 p.m.