Triple

T11419271
Position Surface form Disambiguated ID Type / Status
Subject Söğütlüçeşme E270574 entity
Predicate roadAccessVia P9041 FINISHED
Object D-100 highway E663163 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: D-100 highway | Statement: [Söğütlüçeşme, roadAccessVia, D-100 highway]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: D-100 highway
Context triple: [Söğütlüçeşme, roadAccessVia, D-100 highway]
  • A. D100 highway chosen
    The D100 highway is a major east–west state road in Turkey that runs through key cities including İzmit, serving as an important intercity and regional transport route.
  • B. M-41 Highway
    M-41 Highway is a major high-altitude road through Central Asia’s Pamir Mountains, renowned as one of the world’s most remote and scenic driving routes.
  • C. C-16 highway
    The C-16 highway is a major road in Catalonia, Spain, that forms part of the E-9 corridor and connects inland cities such as Manresa with Barcelona and the Pyrenees.
  • D. D605 highway
    The D605 highway is a major Turkish road that runs through Kocaeli Province, connecting local towns and facilitating regional transportation.
  • E. M10 highway
    The M10 highway is a major Russian federal road that connects Moscow and Saint Petersburg, passing through cities such as Tver.
  • 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_69d6aaddeaa8819088b30ef7b50598c9 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d801b20ce08190befc98379b879985 completed April 9, 2026, 7:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69e6e7580c508190a81eadd9015c75ef completed April 21, 2026, 2:56 a.m.
Created at: April 8, 2026, 9:34 p.m.