Triple

T7937934
Position Surface form Disambiguated ID Type / Status
Subject OpenStack E184327 entity
Predicate component P35 FINISHED
Object Zaqar
Zaqar is OpenStack’s multi-tenant messaging and notification service that provides queuing and publish-subscribe capabilities for cloud applications.
 E699725 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: Zaqar | Statement: [OpenStack, component, Zaqar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zaqar
Context triple: [OpenStack, component, Zaqar]
  • A. Ghogha
    Ghogha is a coastal town in Gujarat, India, known as a historic port settlement near Bhavnagar on the Gulf of Khambhat.
  • B. Dhuʼb
    Dhuʼb is a subtribe historically associated with the larger Arab tribe of Kinana.
  • C. Shushary
    Shushary is a municipal settlement in the southern part of Saint Petersburg, Russia, known for its residential areas and industrial facilities.
  • D. Zau
    Zau is an ancient city, historically known as Sais, that served as an important religious and political center in Egypt’s Nile Delta.
  • E. Qafar
    Qafar is another name for the Afar people, a Cushitic ethnic group primarily inhabiting the Horn of Africa, especially in Ethiopia, Eritrea, and Djibouti.
  • 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: Zaqar
Triple: [OpenStack, component, Zaqar]
Generated description
Zaqar is OpenStack’s multi-tenant messaging and notification service that provides queuing and publish-subscribe capabilities for cloud applications.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zaqar
Target entity description: Zaqar is OpenStack’s multi-tenant messaging and notification service that provides queuing and publish-subscribe capabilities for cloud applications.
  • A. Ghogha
    Ghogha is a coastal town in Gujarat, India, known as a historic port settlement near Bhavnagar on the Gulf of Khambhat.
  • B. Dhuʼb
    Dhuʼb is a subtribe historically associated with the larger Arab tribe of Kinana.
  • C. Shushary
    Shushary is a municipal settlement in the southern part of Saint Petersburg, Russia, known for its residential areas and industrial facilities.
  • D. Zau
    Zau is an ancient city, historically known as Sais, that served as an important religious and political center in Egypt’s Nile Delta.
  • E. Qafar
    Qafar is another name for the Afar people, a Cushitic ethnic group primarily inhabiting the Horn of Africa, especially in Ethiopia, Eritrea, and Djibouti.
  • 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_69cb3aef2394819086eea1f6ab117aed completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5c0a96ac819099ad30fb925eb329 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.