Triple
T24326809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ernest film series |
E613122
|
entity |
| Predicate | includesMilitaryFilm |
P146691
|
FINISHED |
| Object | Ernest in the Army |
—
|
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: Ernest in the Army | Statement: [Ernest film series, includesMilitaryFilm, Ernest in the Army]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesMilitaryFilm Context triple: [Ernest film series, includesMilitaryFilm, Ernest in the Army]
-
A.
includesMilitaryOrder
Indicates that one entity contains, encompasses, or formally incorporates a military order within its scope or structure.
-
B.
hasMilitaryTheme
chosen
Indicates that something incorporates or is characterized by elements related to the military, such as soldiers, warfare, equipment, or military settings.
-
C.
viewsMilitaryAs
Indicates that one entity holds a particular perception, attitude, or evaluative stance toward the military as an institution or concept.
-
D.
militaryTheater
Indicates that an entity is a geographic or operational area where military operations or campaigns are conducted.
-
E.
includedInFilm
Indicates that one entity (such as a scene, segment, or element) is contained within or forms part of a particular film.
- 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_69e2d7db6d5c819091194918157a7c1f |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f292edb6f481909f0a6a7592fd7d6a |
completed | April 29, 2026, 11:23 p.m. |
| PD | Predicate disambiguation | batch_69f287ad30048190b3ad3613486f277f |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 1:54 a.m.