Triple

T10349809
Position Surface form Disambiguated ID Type / Status
Subject La Chêneraie E243849 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object GE E129065 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: GE | Statement: [La Chêneraie, vehicleRegistrationCode, GE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GE
Context triple: [La Chêneraie, vehicleRegistrationCode, GE]
  • A. GE
    GE is the ISO 3166-1 alpha-2 country code for Georgia, a nation at the crossroads of Eastern Europe and Western Asia.
  • B. GE
    GE is the abbreviation for ICANN’s Government Engagement function, which manages and coordinates ICANN’s relationships and interactions with governments and intergovernmental organizations worldwide.
  • C. GE
    GE is the commonly used abbreviation for Global Entry, a U.S. government program that provides expedited clearance for pre-approved, low-risk international travelers entering the United States.
  • D. GE chosen
    GE is the Swiss canton code for Geneva, a major city and canton in western Switzerland known for its international organizations and financial center.
  • E. GM
    GM is the vehicle registration code used on license plates for vehicles registered in the Oberbergischer Kreis district in North Rhine-Westphalia, Germany.
  • 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e946cbb881909b88536d0107995d completed April 7, 2026, 11:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d75095625c819082d4d0976a193e6c completed April 9, 2026, 7:09 a.m.
Created at: April 6, 2026, 11:57 a.m.