Triple
T7361567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World War II films |
E169761
|
entity |
| Predicate | hasCommonSubject |
P30529
|
FINISHED |
| Object | military combat |
—
|
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: military combat | Statement: [World War II films, hasCommonSubject, military combat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonSubject Context triple: [World War II films, hasCommonSubject, military combat]
-
A.
hasTypicalSubject
chosen
Indicates that something is commonly or characteristically used as the subject (agent or topic) of a given relation or action.
-
B.
hasCommonReference
Indicates that two or more entities share the same source, citation, or referential basis.
-
C.
sharesCommonAncestorWith
Indicates that two entities have at least one ancestor in common in their lineage or hierarchy.
-
D.
hasCommonSpace
Indicates that two or more entities share access to the same physical or virtual area intended for joint or overlapping use.
-
E.
hasPrimarySubject
Indicates that an entity is the main or principal subject associated with another entity or resource.
- 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_69c68a59f2288190877ca15c19b1e822 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f26d6d6081909c7272a9ccae0d97 |
completed | March 27, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69c6f02d36108190bcb34a95e6a30bd7 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:06 p.m.