Triple

T7939665
Position Surface form Disambiguated ID Type / Status
Subject Helm E184358 entity
Predicate supportsFormat P203 FINISHED
Object YAML E208075 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: YAML | Statement: [Helm, supportsFormat, YAML]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: YAML
Context triple: [Helm, supportsFormat, YAML]
  • A. YAML chosen
    YAML is a human-readable data serialization language commonly used for configuration files and data exchange, emphasizing simplicity and ease of editing.
  • B. TOML
    TOML is a human-readable configuration file format designed for simplicity and unambiguous parsing, commonly used in modern software tooling and package managers.
  • C. YAM
    YAM is the IATA airport code for Sault Ste. Marie Airport in Ontario, Canada.
  • D. JSON5
    JSON5 is an extension of the JSON data format that adds more human-friendly features like comments, trailing commas, and unquoted object keys while remaining largely compatible with standard JSON.
  • E. YANG
    YANG is a data modeling language widely used in networking, particularly with NETCONF and RESTCONF, to define the structure and semantics of configuration and state data on network devices.
  • 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3b0983388190a77e8d5d899c5130 completed March 31, 2026, 3:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5c0e868481908748d340244ea8ea completed March 31, 2026, 5:30 a.m.
Created at: March 30, 2026, 5:08 p.m.