Triple
T5156575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Top Gun (1955 film) |
E116324
|
entity |
| Predicate | settingLocation |
P40
|
FINISHED |
| Object | Arizona |
E7404
|
NE 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: Arizona | Statement: [Top Gun (1955 film), settingLocation, Arizona]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arizona Context triple: [Top Gun (1955 film), settingLocation, Arizona]
-
A.
Arizona
"Arizona" is a 2018 dark comedy thriller film set during the 2009 housing crisis, starring Rosemarie DeWitt and Danny McBride.
-
B.
Arizona
chosen
Arizona is a southwestern U.S. state known for its desert climate, the Grand Canyon, and major cities like Phoenix and Tucson.
-
C.
Arizona Territory
The Arizona Territory was a historical U.S. territorial jurisdiction in the American Southwest that existed from the mid-19th century until it achieved statehood as Arizona in 1912.
-
D.
New Mexico
New Mexico is a southwestern U.S. state known for its diverse landscapes, rich Native American and Hispanic cultural heritage, and historic cities like Santa Fe and Albuquerque.
-
E.
Nevada
Nevada is a small city in western Missouri known as the county seat of Vernon County and for its historic downtown and regional agricultural economy.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69bd445d94788190b72e2cc563120995 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79019c6481909641f173c5b3769a |
completed | March 20, 2026, 4:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bee07283c08190a8fc23d3041275ee |
completed | March 21, 2026, 6:16 p.m. |
Created at: March 20, 2026, 1:44 p.m.