Triple
T38540046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Bofors Gun |
E924805
|
entity |
| Predicate | conflictTypeDepicted |
P1397
|
FINISHED |
| Object | interpersonal conflict among soldiers |
—
|
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: interpersonal conflict among soldiers | Statement: [The Bofors Gun, conflictTypeDepicted, interpersonal conflict among soldiers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conflictTypeDepicted Context triple: [The Bofors Gun, conflictTypeDepicted, interpersonal conflict among soldiers]
-
A.
depictsConflict
Indicates that one entity visually represents or portrays a situation of conflict involving another entity or entities.
-
B.
conflictType
chosen
Indicates the specific kind or category of conflict that characterizes the relationship or interaction between entities.
-
C.
militaryConflict
Indicates a relationship where two or more parties are engaged in organized, armed hostilities or warfare against each other.
-
D.
loreConflict
Indicates that there is an inconsistency, contradiction, or incompatibility between pieces of lore or canonical information.
-
E.
conflictsInvolvedIn
Indicates that an entity participates as a party or actor in one or more conflicts.
- 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_69f76eadeac081909cdfdd0474cb6765 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcd2e930608190b2b2af0d4753d7f0 |
completed | May 7, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f81cbc8190b4fd3bfc3106c1f3 |
completed | May 7, 2026, 5:55 p.m. |
Created at: May 3, 2026, 4:32 p.m.