Triple

T18670200
Position Surface form Disambiguated ID Type / Status
Subject SR 303 E456453 entity
Predicate abbreviation P43 FINISHED
Object Loop 303 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: Loop 303 | Statement: [SR 303, abbreviation, Loop 303]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Loop 303
Context triple: [SR 303, abbreviation, Loop 303]
  • A. Loop 303 chosen
    Loop 303 is a major freeway in the Phoenix metropolitan area that serves as part of the region’s outer beltway system, facilitating circumferential travel and suburban growth.
  • B. Loop 323
    Loop 323 is a primary circumferential highway that serves as the main loop route around the city of Tyler, Texas.
  • C. Loop 336
    Loop 336 is a major circumferential roadway that serves as a key traffic artery around the city of Conroe, Texas.
  • D. Loop 286
    Loop 286 is a state highway loop that serves as a beltway around the city of Paris in Lamar County, Texas.
  • E. Loop 1604
    Loop 1604 is a major highway encircling much of San Antonio, Texas, serving as a key route for regional traffic and access to suburban districts and commercial areas.
  • 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_69d8d38f72b4819090a935175d9ca8af completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e556b1140c81908002c27a33c03ae2 completed April 19, 2026, 10:26 p.m.
Created at: April 10, 2026, 11:48 a.m.