Triple
T37716962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jan |
E939478
|
entity |
| Predicate | combatantInFiction |
P170730
|
FINISHED |
| Object | World War II |
—
|
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: World War II | Statement: [Jan, combatantInFiction, World War II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: combatantInFiction Context triple: [Jan, combatantInFiction, World War II]
-
A.
alliesInFiction
Indicates that two or more entities are portrayed as allies or cooperative partners within a fictional context or narrative.
-
B.
competesWithInFiction
Indicates that one fictional character or entity is portrayed as a rival or opponent of another within a narrative or fictional context.
-
C.
contestedByFictionalCharacter
Indicates that a fictional character challenges, disputes, or opposes something, such as a claim, decision, or situation.
-
D.
fictionalConflict
Indicates a relationship where one fictional entity is in opposition, dispute, or struggle with another within a narrative context.
-
E.
warServedInFictionally
chosen
Indicates that a fictional character is depicted as having served in a particular war within a narrative or story.
- 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_69f76edc208c8190bc8b9683f75e1024 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcab6e888881908ca9e18660928a40 |
completed | May 7, 2026, 3:10 p.m. |
| PD | Predicate disambiguation | batch_69fc4562a5b88190bad48f083a6dcdfa |
completed | May 7, 2026, 7:55 a.m. |
Created at: May 3, 2026, 4:18 p.m.