Triple

T11313493
Position Surface form Disambiguated ID Type / Status
Subject Autoroute A9 E267901 entity
Predicate crossesDepartment P27425 FINISHED
Object Gard E89752 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: Gard | Statement: [Autoroute A9, crossesDepartment, Gard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gard
Context triple: [Autoroute A9, crossesDepartment, Gard]
  • A. Gard chosen
    Gard is a department in southern France known for its Mediterranean landscapes, historic towns, and the famous Pont du Gard Roman aqueduct.
  • B. Gardingen
    Gardingen is a small locality in northern Germany best known as the birthplace of the renowned classical scholar and historian Theodor Mommsen.
  • C. Gaten
    Gaten is the first name of Gaten Matarazzo, an American actor best known for his role as Dustin Henderson on the Netflix series "Stranger Things."
  • D. Grenaa
    Grenaa is a coastal town in eastern Jutland, Denmark, known for its ferry connections to the island of Anholt and its role as a regional commercial and educational center.
  • E. Tofte
    Tofte is a village in the former Hurum municipality in Norway, known for its coastal location along the Oslofjord and industrial history.
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9c1b7dc81908d8cc768c47390d3 completed April 9, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69e50a910a2c8190b8afd4c988e64141 completed April 19, 2026, 5:02 p.m.
Created at: April 8, 2026, 9:32 p.m.