Triple

T17675523
Position Surface form Disambiguated ID Type / Status
Subject Active Job E440633 entity
Predicate supportsBackend P15794 FINISHED
Object Que
Que is a fast, Ruby-based background job processing library designed for reliability and efficient job execution.
E1282462 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: Que | Statement: [Active Job, supportsBackend, Que]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Que
Context triple: [Active Job, supportsBackend, Que]
  • A. Que
    Que was an Iron Age Neo-Hittite kingdom located in Cilicia in southeastern Anatolia, known from Assyrian records and archaeological remains.
  • B. Que
    Que is a musical artist best known for performing the track "Loyal."
  • C. QUE
    QUE is the station code for Queen station, a public transit stop in Toronto's subway system.
  • D. QUE
    QUE is the standard abbreviation used for the Quebec Remparts, a major junior ice hockey team in the Quebec Major Junior Hockey League.
  • E. Q
    Q is a powerful, omnipotent trickster from the Q Continuum who frequently tests and torments the crew of the USS Enterprise in Star Trek: The Next Generation.
  • 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: Que
Triple: [Active Job, supportsBackend, Que]
Generated description
Que is a fast, Ruby-based background job processing library designed for reliability and efficient job execution.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Que
Target entity description: Que is a fast, Ruby-based background job processing library designed for reliability and efficient job execution.
  • A. Que
    Que was an Iron Age Neo-Hittite kingdom located in Cilicia in southeastern Anatolia, known from Assyrian records and archaeological remains.
  • B. Que
    Que is a musical artist best known for performing the track "Loyal."
  • C. QUE
    QUE is the standard abbreviation used for the Quebec Remparts, a major junior ice hockey team in the Quebec Major Junior Hockey League.
  • D. QUE
    QUE is the station code for Queen station, a public transit stop in Toronto's subway system.
  • E. Q
    Q is a powerful, omnipotent trickster from the Q Continuum who frequently tests and torments the crew of the USS Enterprise in Star Trek: The Next Generation.
  • 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_69d8b9e87e18819087104a44dc4dc5b1 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e46f6cca54819094ea0bed1517724e completed April 19, 2026, 6 a.m.
NED1 Entity disambiguation (via context triple) batch_6a022325d6108190975082abcdb21ce1 completed May 11, 2026, 6:42 p.m.
NEDg Description generation batch_6a022759531c8190a77c5dc4e3ccaee6 completed May 11, 2026, 7 p.m.
NED2 Entity disambiguation (via description) batch_6a0227ff79d881908ad190b2665bc63d completed May 11, 2026, 7:03 p.m.
Created at: April 10, 2026, 10 a.m.