Triple

T15089429
Position Surface form Disambiguated ID Type / Status
Subject Radia Perlman E360376 entity
Predicate givenName P17 FINISHED
Object Radia
Radia is a pioneering computer scientist best known for her foundational work in network protocols, particularly the Spanning Tree Protocol used in Ethernet networks.
 E1136475 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: Radia | Statement: [Radia Perlman, givenName, Radia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Radia
Context triple: [Radia Perlman, givenName, Radia]
  • A. Keila
    Keila is a small town in northern Estonia known for its historic church, scenic Keila River and waterfall, and role as a local administrative and transport hub.
  • B. Rahki
    Rahki is a Grammy-winning American record producer and songwriter best known for his work with Kendrick Lamar and other prominent hip-hop artists.
  • C. Ramonda
    Ramonda is a Marvel Comics character best known as the Queen Mother of Wakanda and the stepmother of T’Challa, the Black Panther.
  • D. Renaelva
    Renaelva is a river in eastern Norway that flows through Hedmark county before joining the larger Glomma river.
  • E. Belita
    Belita was a British Olympic figure skater and film actress known for her graceful performances in 1940s and 1950s Hollywood ice-skating musicals.
  • 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: Radia
Triple: [Radia Perlman, givenName, Radia]
Generated description
Radia is a pioneering computer scientist best known for her foundational work in network protocols, particularly the Spanning Tree Protocol used in Ethernet networks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Radia
Target entity description: Radia is a pioneering computer scientist best known for her foundational work in network protocols, particularly the Spanning Tree Protocol used in Ethernet networks.
  • A. Keila
    Keila is a small town in northern Estonia known for its historic church, scenic Keila River and waterfall, and role as a local administrative and transport hub.
  • B. Rahki
    Rahki is a Grammy-winning American record producer and songwriter best known for his work with Kendrick Lamar and other prominent hip-hop artists.
  • C. Ramonda
    Ramonda is a Marvel Comics character best known as the Queen Mother of Wakanda and the stepmother of T’Challa, the Black Panther.
  • D. Renaelva
    Renaelva is a river in eastern Norway that flows through Hedmark county before joining the larger Glomma river.
  • E. Belita
    Belita was a British Olympic figure skater and film actress known for her graceful performances in 1940s and 1950s Hollywood ice-skating musicals.
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00277ea808190be3f002a8316eff1 completed April 15, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69feae1d7a0c819096b035f8ca8d0e90 completed May 9, 2026, 3:46 a.m.
NEDg Description generation batch_69feaf8e1b508190b0b5ceb64d44fad6 completed May 9, 2026, 3:52 a.m.
NED2 Entity disambiguation (via description) batch_69feb038065c8190b60266644db64092 completed May 9, 2026, 3:55 a.m.
Created at: April 10, 2026, 3:04 a.m.