Triple

T13441086
Position Surface form Disambiguated ID Type / Status
Subject Stiege E320361 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object HZ E318585 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: HZ | Statement: [Stiege, vehicleRegistrationCode, HZ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HZ
Context triple: [Stiege, vehicleRegistrationCode, HZ]
  • A. HZ chosen
    HZ is the vehicle registration code assigned to the town of Thale in Germany.
  • B. ZH
    ZH is the provincial code for Zuid-Holland, a densely populated and economically important province in the western Netherlands that includes cities like Rotterdam and The Hague.
  • C. ZH
    ZH is the official vehicle registration code used for the Swiss canton of Zurich.
  • D. HY
    HY is the commonly used abbreviation for the University of Helsinki, a major research university in Finland.
  • E. HY
    HY is the vehicle registration code used on license plates for vehicles registered in the Finnish town of Hyvinkää.
  • 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_69d80761e6cc8190a90c844589998ecc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaee704ac8190b4c7f4e0d3a88494 completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f74621474c8190b96a8f8561451bed completed May 3, 2026, 12:57 p.m.
Created at: April 9, 2026, 9:40 p.m.