Triple

T9024080
Position Surface form Disambiguated ID Type / Status
Subject Soviet design institutes E215999 entity
Predicate notableExample P1503 FINISHED
Object Gipromez
Gipromez was a prominent Soviet industrial design institute known for planning and engineering major metallurgical and heavy industry facilities.
 E773227 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: Gipromez | Statement: [Soviet design institutes, notableExample, Gipromez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gipromez
Context triple: [Soviet design institutes, notableExample, Gipromez]
  • A. Gamelia
    Gamelia is an epithet associated with the Greek goddess Hera, emphasizing her role as protector of marriage and weddings.
  • B. Giporlos
    Giporlos is a coastal municipality in the province of Eastern Samar in the Philippines, known for its fishing communities and scenic seaside landscapes.
  • C. Giric
    Giric was a 9th-century king of the Picts or early Scots, remembered as a shadowy and possibly legendary ruler whose reign is associated with Eochaid of Scotland.
  • D. Gsell
    Gsell is a surname of Germanic origin borne by various notable individuals, including artists, scholars, and public figures.
  • E. Gimonde
    Gimonde is a rural civil parish in the municipality of Bragança in northeastern Portugal, known for its traditional architecture and natural landscapes.
  • 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: Gipromez
Triple: [Soviet design institutes, notableExample, Gipromez]
Generated description
Gipromez was a prominent Soviet industrial design institute known for planning and engineering major metallurgical and heavy industry facilities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gipromez
Target entity description: Gipromez was a prominent Soviet industrial design institute known for planning and engineering major metallurgical and heavy industry facilities.
  • A. Gamelia
    Gamelia is an epithet associated with the Greek goddess Hera, emphasizing her role as protector of marriage and weddings.
  • B. Giporlos
    Giporlos is a coastal municipality in the province of Eastern Samar in the Philippines, known for its fishing communities and scenic seaside landscapes.
  • C. Giric
    Giric was a 9th-century king of the Picts or early Scots, remembered as a shadowy and possibly legendary ruler whose reign is associated with Eochaid of Scotland.
  • D. Gsell
    Gsell is a surname of Germanic origin borne by various notable individuals, including artists, scholars, and public figures.
  • E. Gimonde
    Gimonde is a rural civil parish in the municipality of Bragança in northeastern Portugal, known for its traditional architecture and natural landscapes.
  • 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_69ca83a5fa88819088144801b4dd7245 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6a7a770081908dfe3ce3374a04ba completed April 1, 2026, 12:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdbbcaedc819084f8b057fbfcb0e7 completed April 3, 2026, 3:24 p.m.
NEDg Description generation batch_69cfdcae0e5c81909c50a0b53c1cf7cc completed April 3, 2026, 3:28 p.m.
NED2 Entity disambiguation (via description) batch_69cfdd6a2ba481908d66fed8f05a1297 completed April 3, 2026, 3:31 p.m.
Created at: March 30, 2026, 7:07 p.m.