Triple

T1092365
Position Surface form Disambiguated ID Type / Status
Subject Orion's Belt E24193 entity
Predicate hasStar P3335 FINISHED
Object Mintaka
Mintaka is a bright multiple star system in the constellation Orion, forming one of the three prominent stars of Orion’s Belt.
 E126207 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: Mintaka | Statement: [Orion's Belt, hasStar, Mintaka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mintaka
Context triple: [Orion's Belt, hasStar, Mintaka]
  • A. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • B. Negombo
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • C. Ntumu
    Ntumu is a dialect of the Fang language spoken by Fang communities in parts of Central Africa, particularly in Equatorial Guinea, Gabon, and Cameroon.
  • D. Murambi
    Murambi is a residential suburb of Mutare, a major city in eastern Zimbabwe.
  • E. Tumut
    Tumut is a historic town in the Snowy Mountains region of New South Wales, Australia, known for its timber industry, scenic river landscapes, and role as a gateway to the Snowy Mountains Scheme.
  • 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: Mintaka
Triple: [Orion's Belt, hasStar, Mintaka]
Generated description
Mintaka is a bright multiple star system in the constellation Orion, forming one of the three prominent stars of Orion’s Belt.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mintaka
Target entity description: Mintaka is a bright multiple star system in the constellation Orion, forming one of the three prominent stars of Orion’s Belt.
  • A. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • B. Negombo
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • C. Ntumu
    Ntumu is a dialect of the Fang language spoken by Fang communities in parts of Central Africa, particularly in Equatorial Guinea, Gabon, and Cameroon.
  • D. Murambi
    Murambi is a residential suburb of Mutare, a major city in eastern Zimbabwe.
  • E. Tumut
    Tumut is a historic town in the Snowy Mountains region of New South Wales, Australia, known for its timber industry, scenic river landscapes, and role as a gateway to the Snowy Mountains Scheme.
  • 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_69a49404428c819092dcc9632f5f7b8b completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b982018481908b222df095e318c0 completed March 1, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c2a20b48190b3a550f6e5ee13e1 completed March 7, 2026, 4:02 p.m.
NEDg Description generation batch_69ac4cae760881909329701561ad2ba6 completed March 7, 2026, 4:05 p.m.
NED2 Entity disambiguation (via description) batch_69ac4d7176808190b74d535d7e1b7c6a completed March 7, 2026, 4:08 p.m.
Created at: March 1, 2026, 7:42 p.m.