Triple

T14436467
Position Surface form Disambiguated ID Type / Status
Subject Agentschap van het Rijk E357975 entity
Predicate differsFrom P278 FINISHED
Object ZBO
ZBO is a Dutch semi-autonomous public authority that performs specific government tasks at arm’s length from direct ministerial control.
 E1099279 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: ZBO | Statement: [Agentschap van het Rijk, differsFrom, ZBO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ZBO
Context triple: [Agentschap van het Rijk, differsFrom, ZBO]
  • A. ZUB
    ZUB is a Swiss train protection and automatic train control system used to enhance operational safety on the Swiss Federal Railways network.
  • B. ZBA
    ZBA is the National Rail station code assigned to Bank Underground station in London.
  • C. ŻOB
    ŻOB was a Jewish resistance organization that led the armed uprising in the Warsaw Ghetto during World War II.
  • D. ZMB
    ZMB is the three-letter ISO 3166-1 alpha-3 country code assigned to Zambia.
  • E. ZBH
    ZBH is the stock ticker symbol for Zimmer Biomet Holdings, Inc., a major medical device company specializing in musculoskeletal healthcare products.
  • 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: ZBO
Triple: [Agentschap van het Rijk, differsFrom, ZBO]
Generated description
ZBO is a Dutch semi-autonomous public authority that performs specific government tasks at arm’s length from direct ministerial control.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ZBO
Target entity description: ZBO is a Dutch semi-autonomous public authority that performs specific government tasks at arm’s length from direct ministerial control.
  • A. ZUB
    ZUB is a Swiss train protection and automatic train control system used to enhance operational safety on the Swiss Federal Railways network.
  • B. ZBA
    ZBA is the National Rail station code assigned to Bank Underground station in London.
  • C. ŻOB
    ŻOB was a Jewish resistance organization that led the armed uprising in the Warsaw Ghetto during World War II.
  • D. ZMB
    ZMB is the three-letter ISO 3166-1 alpha-3 country code assigned to Zambia.
  • E. ZBH
    ZBH is the stock ticker symbol for Zimmer Biomet Holdings, Inc., a major medical device company specializing in musculoskeletal healthcare products.
  • 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_69d8279402a88190821ffa39ae15bccf completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de9148cf4481909082cc91b2f76218 completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bd7f46881908df1a1cea7b6af9b completed May 8, 2026, 3:43 a.m.
NEDg Description generation batch_69fd5d585cc08190908bc5f9b8abdb82 completed May 8, 2026, 3:49 a.m.
NED2 Entity disambiguation (via description) batch_69fd5e0bbd6c8190b14039b3335692c7 completed May 8, 2026, 3:52 a.m.
Created at: April 10, 2026, 1:18 a.m.