Triple

T9925960
Position Surface form Disambiguated ID Type / Status
Subject HDFS E187921 entity
Predicate hasComponent P35 FINISHED
Object JournalNode E185678 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: JournalNode | Statement: [HDFS, hasComponent, JournalNode]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: JournalNode
Context triple: [HDFS, hasComponent, JournalNode]
  • A. Jepsen
    Jepsen is a surname most notably associated with individuals such as display technology innovator Mary Lou Jepsen.
  • B. Netnod
    Netnod is a Swedish internet infrastructure organization that operates critical core services such as internet exchange points, DNS root server instances, and time and frequency distribution.
  • C. JEP
    JEP is a leading peer-reviewed academic journal that publishes accessible, survey-style articles on a wide range of economics topics for both specialists and informed non-specialists.
  • D. Uzlovaya
    Uzlovaya is a town in western Russia known as an industrial and railway hub within Tula Oblast.
  • E. Apache ZooKeeper chosen
    Apache ZooKeeper is a centralized service for maintaining configuration information, naming, and distributed synchronization in large-scale distributed systems.
  • 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_69ca82b22a688190b52c75bd48429c10 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb599e32c8190ac676fa89c131bb6 completed April 2, 2026, 12:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20e143660819097a9fa96365bc25a completed April 5, 2026, 7:24 a.m.
Created at: March 30, 2026, 8:43 p.m.