Triple
T12535271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation AI |
E299670
|
entity |
| Predicate | filmDepictionFocus |
P22751
|
FINISHED |
| Object | operational planning and execution of Pearl Harbor attack |
—
|
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: operational planning and execution of Pearl Harbor attack | Statement: [Operation AI, filmDepictionFocus, operational planning and execution of Pearl Harbor attack]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmDepictionFocus Context triple: [Operation AI, filmDepictionFocus, operational planning and execution of Pearl Harbor attack]
-
A.
filmPortrayer
Indicates that one entity portrays or plays the role of another entity (such as a character or person) in a film.
-
B.
subjectOfFilm
chosen
Indicates that a person, character, or topic is the main focus or central topic depicted in a particular film.
-
C.
depictionFocus
Indicates that a depiction (such as an image or illustration) is primarily focused on or centered around a particular entity or subject.
-
D.
filmType
Indicates the specific category or genre that a film belongs to.
-
E.
filmLengthFocus
Indicates that the relationship or action centers on the duration or running time of a 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_69d6ada707008190aaec1238117c9379 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d9540d7b788190a0d57b098e90e491 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.