Triple
T20292401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mesa Arizona Temple |
E510058
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Mesa |
—
|
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: Mesa | Statement: [Mesa Arizona Temple, city, Mesa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mesa Context triple: [Mesa Arizona Temple, city, Mesa]
-
A.
Mesa
Mesa is a small community located within Franklin County in the U.S. state of Washington.
-
B.
Mesa
Mesa is a pioneering systems programming language developed at Xerox PARC in the 1970s, notable for its strong typing, modularity, and influence on later languages and operating system design.
-
C.
Mesa, Arizona
chosen
Mesa, Arizona is a large city in the Phoenix metropolitan area known for its desert climate, suburban communities, and role as a major spring training hub for Major League Baseball.
-
D.
Sedona
Sedona is a scenic Arizona city famed for its striking red rock formations, vibrant arts community, and reputation as a spiritual and outdoor recreation destination.
-
E.
Mesa Central
Mesa Central is a high, semi-arid plateau region in central Mexico known for its basins, volcanic ranges, and significant agricultural and urban centers.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c652388190b782cad965e5a098 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e677024de08190bfa54ae26b5486d1 |
completed | April 20, 2026, 6:57 p.m. |
Created at: April 16, 2026, 11:12 a.m.