Triple

T9814789
Position Surface form Disambiguated ID Type / Status
Subject Ingelheim am Rhein E238373 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object BIN
BIN is the vehicle registration code used on license plates for vehicles registered in the town of Ingelheim am Rhein in Germany.
E823573 NE FINISHED

How this triple was built (4 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: BIN | Statement: [Ingelheim am Rhein, vehicleRegistrationCode, BIN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BIN
Context triple: [Ingelheim am Rhein, vehicleRegistrationCode, BIN]
  • A. BN2
    BN2 is a UK postal district covering parts of eastern Brighton and nearby areas within the BN (Brighton) postcode region.
  • B. BIT
    BIT is the stock exchange code commonly used to identify securities listed on Borsa Italiana, the main Italian stock exchange based in Milan.
  • C. BN
    BN is the vehicle registration code used on license plates for the German city of Bonn.
  • D. BJ
    BJ is the stock ticker symbol for BJ's Wholesale Club, a U.S.-based membership-only warehouse club chain.
  • E. Β
    Β is the Greek capital letter beta, commonly used in mathematics, science, and as part of Greek-letter names for organizations.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: BIN
Triple: [Ingelheim am Rhein, vehicleRegistrationCode, BIN]
Generated description
BIN is the vehicle registration code used on license plates for vehicles registered in the town of Ingelheim am Rhein in Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: BIN
Target entity description: BIN is the vehicle registration code used on license plates for vehicles registered in the town of Ingelheim am Rhein in Germany.
  • A. BN2
    BN2 is a UK postal district covering parts of eastern Brighton and nearby areas within the BN (Brighton) postcode region.
  • B. BIT
    BIT is the stock exchange code commonly used to identify securities listed on Borsa Italiana, the main Italian stock exchange based in Milan.
  • C. BN
    BN is the vehicle registration code used on license plates for the German city of Bonn.
  • D. BJ
    BJ is the stock ticker symbol for BJ's Wholesale Club, a U.S.-based membership-only warehouse club chain.
  • E. Β
    Β is the Greek capital letter beta, commonly used in mathematics, science, and as part of Greek-letter names for organizations.
  • F. None of above. chosen

Provenance (5 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_69ca84dfde1481909f47c286d715f892 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb2f19660819083e3f15780352052 completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc67db68819093217c9a74e72fbf completed April 5, 2026, 2:43 a.m.
NEDg Description generation batch_69d1ccf59c68819082b4aa37e06d2aaf completed April 5, 2026, 2:46 a.m.
NED2 Entity disambiguation (via description) batch_69d1d0d945d48190b56b7fd2ce568a13 completed April 5, 2026, 3:02 a.m.
Created at: March 30, 2026, 8:30 p.m.