Triple

T575071
Position Surface form Disambiguated ID Type / Status
Subject Java E13745 entity
Predicate influencedBy P9 FINISHED
Object Mesa E53029 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: Mesa | Statement: [Java, influencedBy, Mesa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mesa
Context triple: [Java, influencedBy, Mesa]
  • A. Mesa chosen
    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.
  • B. Mesa, Arizona
    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.
  • C. 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.
  • D. Flagstaff
    Flagstaff is a high-elevation city in northern Arizona known for its proximity to the Grand Canyon, its historic Route 66 corridor, and its role as a center for astronomy and outdoor recreation.
  • E. San Carlos
    San Carlos is a city in San Mateo County, California, located on the San Francisco Peninsula between Belmont and Redwood City.
  • 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b4c23548190a3b883239c7c78c8 completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69a50e23bce481908404040b848ba9c1 completed March 2, 2026, 4:12 a.m.
Created at: March 1, 2026, 7:33 p.m.