Triple

T3267207
Position Surface form Disambiguated ID Type / Status
Subject Handle System E68554 entity
Predicate maintainedBy P86 FINISHED
Object DONAnet
DONAnet is the organization responsible for operating and overseeing the global Handle System infrastructure used for persistent digital identifiers.
 E341328 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: DONAnet | Statement: [Handle System, maintainedBy, DONAnet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DONAnet
Context triple: [Handle System, maintainedBy, DONAnet]
  • A. ANA
    ANA is the standard three-letter abbreviation used for the Anaheim Ducks, a professional ice hockey team in the National Hockey League.
  • B. ANA
    ANA is the commonly used abbreviation for the Afghan National Army, the former main land warfare branch of Afghanistan’s armed forces.
  • C. ANA
    ANA is the ICAO airline designator for All Nippon Airways, Japan’s largest airline and a major global carrier.
  • D. ANA
    ANA is the Portuguese company responsible for managing and operating the main airports in Portugal.
  • E. DANE
    DANE (DNS-based Authentication of Named Entities) is an Internet security protocol that uses DNSSEC to bind X.509 certificates to domain names, enabling more secure and flexible authentication for TLS and other services.
  • 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: DONAnet
Triple: [Handle System, maintainedBy, DONAnet]
Generated description
DONAnet is the organization responsible for operating and overseeing the global Handle System infrastructure used for persistent digital identifiers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DONAnet
Target entity description: DONAnet is the organization responsible for operating and overseeing the global Handle System infrastructure used for persistent digital identifiers.
  • A. ANA
    ANA is the standard three-letter abbreviation used for the Anaheim Ducks, a professional ice hockey team in the National Hockey League.
  • B. ANA
    ANA is the commonly used abbreviation for the Afghan National Army, the former main land warfare branch of Afghanistan’s armed forces.
  • C. ANA
    ANA is the ICAO airline designator for All Nippon Airways, Japan’s largest airline and a major global carrier.
  • D. ANA
    ANA is the Portuguese company responsible for managing and operating the main airports in Portugal.
  • E. DANE
    DANE (DNS-based Authentication of Named Entities) is an Internet security protocol that uses DNSSEC to bind X.509 certificates to domain names, enabling more secure and flexible authentication for TLS and other services.
  • 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_69ad8590444081909e8107a8aeef3a23 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adafce46dc8190a157e4f5012baed5 completed March 8, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b28ef261ec819091c62620765e2cef completed March 12, 2026, 10:01 a.m.
NEDg Description generation batch_69b28f9efe408190bcb1e16931b2fe62 completed March 12, 2026, 10:04 a.m.
NED2 Entity disambiguation (via description) batch_69b2a8b873b081909bbb5de329e45169 completed March 12, 2026, 11:51 a.m.
Created at: March 8, 2026, 3:09 p.m.