Triple

T8439504
Position Surface form Disambiguated ID Type / Status
Subject Robert Urich E199313 entity
Predicate notableWork P4 FINISHED
Object Vega$
Vega$ is a television role played by American actor Robert Urich, best known for his work in popular TV series during the 1970s and 1980s.
 E733479 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: Vega$ | Statement: [Robert Urich, notableWork, Vega$]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vega$
Context triple: [Robert Urich, notableWork, Vega$]
  • A. Yle Vega
    Yle Vega is a Finnish Swedish-language radio channel operated by the national public broadcaster Yleisradio (Yle), offering news, culture, and entertainment programming.
  • B. Vega
    Vega is a European small-lift launch vehicle developed by the European Space Agency and partners, primarily used to place light payloads into low Earth orbit.
  • C. Vega
    Vega is a common Spanish surname borne by numerous notable individuals across fields such as entertainment, sports, and politics.
  • D. Vega
    Vega is a residential locality in Haninge Municipality, Stockholm County, Sweden, known for its commuter rail station and growing suburban housing developments.
  • E. Vega 2
    Vega 2 was a Soviet space probe launched in 1984 that conducted flybys of Venus and Halley’s Comet, studying their atmospheres and environments as part of the Vega program.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Vega$
Triple: [Robert Urich, notableWork, Vega$]
Generated description
Vega$ is a television role played by American actor Robert Urich, best known for his work in popular TV series during the 1970s and 1980s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vega$
Target entity description: Vega$ is a television role played by American actor Robert Urich, best known for his work in popular TV series during the 1970s and 1980s.
  • A. Yle Vega
    Yle Vega is a Finnish Swedish-language radio channel operated by the national public broadcaster Yleisradio (Yle), offering news, culture, and entertainment programming.
  • B. Vega
    Vega is a European small-lift launch vehicle developed by the European Space Agency and partners, primarily used to place light payloads into low Earth orbit.
  • C. Vega
    Vega is a common Spanish surname borne by numerous notable individuals across fields such as entertainment, sports, and politics.
  • D. Vega
    Vega is a residential locality in Haninge Municipality, Stockholm County, Sweden, known for its commuter rail station and growing suburban housing developments.
  • E. Vega 2
    Vega 2 was a Soviet space probe launched in 1984 that conducted flybys of Venus and Halley’s Comet, studying their atmospheres and environments as part of the Vega program.
  • 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_69ca8314cd6c8190a6b8c2a1096e18f3 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe13708988190a534e38d8254c9bd completed March 31, 2026, 2:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce1d9140b48190ad0c493948a3de5e completed April 2, 2026, 7:41 a.m.
NEDg Description generation batch_69ce1f12e1a081909d28b06c520353ef completed April 2, 2026, 7:47 a.m.
NED2 Entity disambiguation (via description) batch_69ce1fb498448190a2737b8895f6bb48 completed April 2, 2026, 7:50 a.m.
Created at: March 30, 2026, 6:08 p.m.