Triple

T10471798
Position Surface form Disambiguated ID Type / Status
Subject A86 E246939 entity
Predicate hasSection P35 FINISHED
Object A86 duplex tunnel E246940 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: A86 duplex tunnel | Statement: [A86, hasSection, A86 duplex tunnel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: A86 duplex tunnel
Context triple: [A86, hasSection, A86 duplex tunnel]
  • A. Duplex A86 tunnel chosen
    The Duplex A86 tunnel is a major double-deck road tunnel in the western suburbs of Paris, designed to complete the A86 ring road while minimizing surface impact.
  • B. A86
    A86 is a major orbital motorway forming part of the ring road system around Paris, France.
  • C. Tunnel No. 2
    Tunnel No. 2 is one of New York City’s major water distribution tunnels that helps convey drinking water from upstate reservoirs to the city’s boroughs.
  • D. TUNAIR
    TUNAIR is the radio callsign used by Tunisair, the national flag carrier airline of Tunisia.
  • E. A682
    The A682 is a primary road in northern England that runs through Lancashire and North Yorkshire, linking towns such as Rawtenstall and serving as a key route across the Pennines.
  • 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_69d381c16c248190a2fe5b471e584e9c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5094cec788190a485c5c9e7cd024a completed April 7, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8a0094910819094d492c87b31898e completed April 10, 2026, 7 a.m.
Created at: April 6, 2026, 12:20 p.m.