Triple
T26851852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pamela Tudsbury |
E676077
|
entity |
| Predicate | warPerspective |
P33446
|
FINISHED |
| Object | civilian and journalistic viewpoint on World War II |
—
|
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: civilian and journalistic viewpoint on World War II | Statement: [Pamela Tudsbury, warPerspective, civilian and journalistic viewpoint on World War II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: warPerspective Context triple: [Pamela Tudsbury, warPerspective, civilian and journalistic viewpoint on World War II]
-
A.
viewOnWar
chosen
Indicates a stance, opinion, or perspective that an entity holds regarding war or armed conflict.
-
B.
warFrontDepicted
Indicates that a particular war front or battlefield area is visually represented or shown in a depiction.
-
C.
warDepicted
Indicates that a work or representation portrays, illustrates, or otherwise depicts a particular war or armed conflict.
-
D.
postWarPerception
Indicates how something is regarded, interpreted, or understood in the period following a war.
-
E.
warPeriod
Indicates a time span during which a state of war or armed conflict is ongoing between parties.
- 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_69eee9b9d7708190a15d7485709ae981 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f61b924d0c819089d6f99cc09bbe59 |
completed | May 2, 2026, 3:43 p.m. |
| PD | Predicate disambiguation | batch_69f611ad2eb48190ac1ed0090f13f7a9 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 5:17 a.m.