Triple

T7022201
Position Surface form Disambiguated ID Type / Status
Subject SR 143 E162853 entity
Predicate hasJunctionWith P1018 FINISHED
Object Loop 202 E100485 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: Loop 202 | Statement: [SR 143, hasJunctionWith, Loop 202]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Loop 202
Context triple: [SR 143, hasJunctionWith, Loop 202]
  • A. Loop 202 chosen
    Loop 202 is a major freeway in the Phoenix, Arizona metropolitan area that forms part of the region’s beltway system, helping route traffic around the city.
  • B. Loop 820
    Loop 820 is a major beltway highway encircling much of the Fort Worth, Texas metropolitan area, serving as a key route for regional traffic and suburban access.
  • C. Loop 101
    Loop 101 is a major freeway encircling much of the Phoenix metropolitan area, connecting numerous suburbs and serving as a key route for regional traffic.
  • D. Loop 12
    Loop 12 is a major circumferential highway in Dallas, Texas, that serves as an important connector between various neighborhoods, freeways, and arterial roads within the city.
  • E. Loop 303
    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.
  • 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_69c6885b26248190a857541e3d10e299 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e1ec34a48190b64cafb94e2f8706 completed March 27, 2026, 8 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7885104e881909be62c2eb12e0bcf completed March 28, 2026, 7:50 a.m.
Created at: March 27, 2026, 2:35 p.m.