Triple
T18385095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Piper Repertory Theater |
E446561
|
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: [Piper Repertory Theater, city, Mesa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mesa Context triple: [Piper Repertory Theater, 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_69d8b9f370b88190b1e5081c2c238e7f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e5179ecde88190b0d88c519d49e995 |
completed | April 19, 2026, 5:57 p.m. |
Created at: April 10, 2026, 10:46 a.m.