Triple

T7938788
Position Surface form Disambiguated ID Type / Status
Subject Cloud Native Computing Foundation E184342 entity
Predicate hostsProject P2592 FINISHED
Object Jaeger
Jaeger is an open-source, cloud-native distributed tracing system used to monitor and troubleshoot complex microservices-based applications.
E699793 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: Jaeger | Statement: [Cloud Native Computing Foundation, hostsProject, Jaeger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jaeger
Context triple: [Cloud Native Computing Foundation, hostsProject, Jaeger]
  • A. Mako
    Mako was a Japanese-American actor and voice actor known for his distinctive voice and roles in films like "Conan the Barbarian" and as the voice of Iroh in "Avatar: The Last Airbender."
  • B. Mako
    Mako is a Japanese imperial family member best known as Princess Mako of Akishino, the former princess who left royal status upon her marriage to a commoner.
  • C. Mako
    Mako is the nickname of Benjamin Mako Hill, a prominent free software activist, scholar, and developer involved with projects like Debian and Wikimedia.
  • D. Mako
    Mako is a high-speed steel roller coaster at SeaWorld Orlando themed around the ocean’s fastest shark.
  • E. Burgard
    Burgard is a German surname borne by individuals such as the computer scientist Wolfram Burgard.
  • 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: Jaeger
Triple: [Cloud Native Computing Foundation, hostsProject, Jaeger]
Generated description
Jaeger is an open-source, cloud-native distributed tracing system used to monitor and troubleshoot complex microservices-based applications.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jaeger
Target entity description: Jaeger is an open-source, cloud-native distributed tracing system used to monitor and troubleshoot complex microservices-based applications.
  • A. Mako
    Mako was a Japanese-American actor and voice actor known for his distinctive voice and roles in films like "Conan the Barbarian" and as the voice of Iroh in "Avatar: The Last Airbender."
  • B. Mako
    Mako is a Japanese imperial family member best known as Princess Mako of Akishino, the former princess who left royal status upon her marriage to a commoner.
  • C. Mako
    Mako is the nickname of Benjamin Mako Hill, a prominent free software activist, scholar, and developer involved with projects like Debian and Wikimedia.
  • D. Mako
    Mako is a high-speed steel roller coaster at SeaWorld Orlando themed around the ocean’s fastest shark.
  • E. Burgard
    Burgard is a German surname borne by individuals such as the computer scientist Wolfram Burgard.
  • 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3af0a2048190838d1aeda59fda0b completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5c0e868481908748d340244ea8ea completed March 31, 2026, 5:30 a.m.
NEDg Description generation batch_69cb7634f4dc8190b5e537f24bccd651 completed March 31, 2026, 7:22 a.m.
NED2 Entity disambiguation (via description) batch_69cbb67e77a48190b93c6ba61becfac4 completed March 31, 2026, 11:56 a.m.
Created at: March 30, 2026, 5:08 p.m.