Triple

T23266840
Position Surface form Disambiguated ID Type / Status
Subject A-5 motorway E588172 entity
Predicate hasJunctionWith P1018 FINISHED
Object M-30 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: M-30 | Statement: [A-5 motorway, hasJunctionWith, M-30]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: M-30
Context triple: [A-5 motorway, hasJunctionWith, M-30]
  • A. M-30 chosen
    M-30 is a major orbital ring road encircling central Madrid and serving as one of the city’s primary traffic arteries.
  • B. M-300
    M-300 is a regional road in the Community of Madrid, Spain, that connects several municipalities in the eastern part of the region.
  • C. Certa Cito
    Certa Cito is the Latin motto of the British Army’s Royal Corps of Signals, reflecting their role in providing swift and reliable military communications.
  • D. Avenio
    Avenio is a low-floor tram and light rail vehicle platform developed by Siemens Mobility for urban public transportation systems worldwide.
  • E. Mobilis
    Mobilis is the integrated public transport fare network for the canton of Vaud in Switzerland, covering multiple operators and modes of transport under a unified ticketing system.
  • 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_69e25d148adc819088efbf42672604e9 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f194cd13b48190a9c282545a34f348 completed April 29, 2026, 5:19 a.m.
Created at: April 17, 2026, 4:37 p.m.