Triple

T14879813
Position Surface form Disambiguated ID Type / Status
Subject Sam Jaeger E349968 entity
Predicate familyName P18 FINISHED
Object Jaeger E699793 NE FINISHED

How this triple was built (2 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: [Sam Jaeger, familyName, Jaeger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jaeger
Context triple: [Sam Jaeger, familyName, Jaeger]
  • A. Jaeger chosen
    Jaeger is an open-source, cloud-native distributed tracing system used to monitor and troubleshoot complex microservices-based applications.
  • B. 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."
  • C. 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.
  • D. Mako
    Mako is the nickname of Benjamin Mako Hill, a prominent free software activist, scholar, and developer involved with projects like Debian and Wikimedia.
  • E. Mako
    Mako is a high-speed steel roller coaster at SeaWorld Orlando themed around the ocean’s fastest shark.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5e622388190b2bf91cd10b9821d completed April 15, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b5670108190b41ef95dc318be60 completed May 8, 2026, 11:01 p.m.
Created at: April 10, 2026, 1:55 a.m.