Triple

T15136310
Position Surface form Disambiguated ID Type / Status
Subject Detroit area freeway network E361563 entity
Predicate hasComponent P35 FINISHED
Object M-59 E680767 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: M-59 | Statement: [Detroit area freeway network, hasComponent, M-59]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: M-59
Context triple: [Detroit area freeway network, hasComponent, M-59]
  • A. M-59 chosen
    M-59 is an east–west state highway in southeastern Michigan that serves as a major suburban arterial route connecting communities north of Detroit.
  • B. M-55
    M-55 is a state trunkline highway in Michigan that runs east–west across the northern Lower Peninsula, connecting several communities including the city of Manistee.
  • C. M-52
    M-52 is a state highway in Michigan that runs north–south through several counties, serving as an important regional route for local and through traffic.
  • D. M-50
    M-50 is a state trunkline highway in Michigan that runs east–west across the southern part of the state, connecting several communities and major routes.
  • E. M-50
    M-50 is a major orbital motorway around Madrid, Spain, designed to divert traffic from the city center and connect key suburbs and highways.
  • 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_69d85a06450081909c5a14ea9851a15e completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e005b3f6f48190b1ed7c7b28feb7a6 completed April 15, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fec88096f081908897fd1c5362c274 completed May 9, 2026, 5:39 a.m.
Created at: April 10, 2026, 3:07 a.m.