Triple

T1074397
Position Surface form Disambiguated ID Type / Status
Subject Normandy E23801 entity
Predicate containsDepartment P1467 FINISHED
Object Manche E81934 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: Manche | Statement: [Normandy, containsDepartment, Manche]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manche
Context triple: [Normandy, containsDepartment, Manche]
  • A. Manche chosen
    Manche is a coastal department in the Normandy region of northwestern France, known for its rugged shoreline along the English Channel and historic sites such as Mont-Saint-Michel.
  • B. Outremer
    Outremer was the collective name for the Crusader states established by Western European Christians in the Levant during the Middle Ages.
  • C. The Sea
    The Sea is a painting by British artist L. S. Lowry, known for its minimalist seascape composition and characteristic muted palette.
  • D. Maalla
    Maalla is a district of the port city of Aden in Yemen, historically significant as part of the former British-controlled Colony of Aden.
  • E. Seabreeze
    Seabreeze was a former neighboring city to Daytona Beach, Florida, that was eventually incorporated into the larger Daytona Beach municipality.
  • 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_69a493f1ddf48190a99d54b00e99f8ce completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b92cbfd481909e2f928c1d06ebaa completed March 1, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac538a5d248190bb44c6b27d2c714c completed March 7, 2026, 4:34 p.m.
Created at: March 1, 2026, 7:42 p.m.