Triple
T17084724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Americanization of Emily (screenplay) |
E414564
|
entity |
| Predicate | antiWarPerspective |
P69158
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [The Americanization of Emily (screenplay), antiWarPerspective, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: antiWarPerspective Context triple: [The Americanization of Emily (screenplay), antiWarPerspective, yes]
-
A.
opposedWar
Indicates that an entity actively resisted, disagreed with, or worked against a particular war or military conflict.
-
B.
opposedWarfareType
Indicates that one entity is in opposition to, or acts against, the type or form of warfare represented by the other entity.
-
C.
concernsWarBetween
Indicates a relationship where something (such as a statement, document, or event) is about or pertains to a war occurring between two or more parties.
-
D.
depictsWarAs
chosen
Indicates that one entity portrays or represents war in a particular way or light.
-
E.
notableViewpoints
Indicates that an entity is associated with significant or noteworthy viewpoints, perspectives, or opinions.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbe60d588190963ccd4c86af1233 |
completed | April 18, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69e35d67b14481909fcdbdeaa5c34785 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:35 a.m.