Triple

T6709108
Position Surface form Disambiguated ID Type / Status
Subject Eisenach E153084 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object EA E22658 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: EA | Statement: [Eisenach, vehicleRegistrationCode, EA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EA
Context triple: [Eisenach, vehicleRegistrationCode, EA]
  • A. EA
    EA was the IATA airline designator for Eastern Air Lines, a major U.S. carrier that operated primarily in the mid-20th century.
  • B. EA chosen
    EA is the commonly used abbreviation for the Environment Agency, the public body responsible for environmental protection and regulation in England.
  • C. Ea
    Ea, also known as Enki, is a major Mesopotamian god associated with wisdom, magic, and freshwater, revered as a creator and benefactor of humanity.
  • D. AE
    AE is the commonly used abbreviation for Academia Europaea, a European non-governmental association of scientists and scholars across all disciplines.
  • E. EMU
    EMU is a public university located in Ypsilanti, Michigan, known for its diverse academic programs and strong emphasis on education, business, and health-related fields.
  • 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_69c68808d8d8819087369015270788fe completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d105b49c8190932246a727e2c513 completed March 27, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7008e6b308190a3d5db2bf4a469c4 completed March 27, 2026, 10:11 p.m.
Created at: March 27, 2026, 2:06 p.m.