Triple

T3623654
Position Surface form Disambiguated ID Type / Status
Subject Alexa Vega E76784 entity
Predicate hasFamilyName P18 FINISHED
Object Vega
Vega is a common Spanish surname borne by numerous notable individuals across fields such as entertainment, sports, and politics.
 E373825 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: [Alexa Vega, hasFamilyName, Vega]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vega
Context triple: [Alexa Vega, hasFamilyName, Vega]
  • A. 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.
  • B. Sirius
    Sirius is the brightest star in the night sky, a nearby binary star system in the constellation Canis Major that has featured prominently in astronomy, mythology, and literature.
  • C. Aldebaran
    Aldebaran is a bright orange giant star in the constellation Taurus, known as one of the most prominent stars in the night sky.
  • D. Betelgeuse
    Betelgeuse is a massive red supergiant star in the constellation Orion, notable for its brightness and status as a likely future supernova.
  • E. Canopus
    Canopus was an ancient Egyptian coastal city near modern-day Alexandria, known as a major religious center and sanctuary dedicated to the goddess Isis.
  • 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: [Alexa Vega, hasFamilyName, Vega]
Generated description
Vega is a common Spanish surname borne by numerous notable individuals across fields such as entertainment, sports, and politics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vega
Target entity description: Vega is a common Spanish surname borne by numerous notable individuals across fields such as entertainment, sports, and politics.
  • A. 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.
  • B. Sirius
    Sirius is the brightest star in the night sky, a nearby binary star system in the constellation Canis Major that has featured prominently in astronomy, mythology, and literature.
  • C. Aldebaran
    Aldebaran is a bright orange giant star in the constellation Taurus, known as one of the most prominent stars in the night sky.
  • D. Betelgeuse
    Betelgeuse is a massive red supergiant star in the constellation Orion, notable for its brightness and status as a likely future supernova.
  • E. Canopus
    Canopus was an ancient Egyptian coastal city near modern-day Alexandria, known as a major religious center and sanctuary dedicated to the goddess Isis.
  • 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_69ad85dae2fc81908d1ceadbc6af0089 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc2bc79008190abe6900adcbda8de completed March 8, 2026, 6:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69b43320955c8190910c0f15c80f41f4 completed March 13, 2026, 3:54 p.m.
NEDg Description generation batch_69b43705642881909c62b7363a4f3a12 completed March 13, 2026, 4:10 p.m.
NED2 Entity disambiguation (via description) batch_69b4379cd04c81909246747bcc357261 completed March 13, 2026, 4:13 p.m.
Created at: March 8, 2026, 3:23 p.m.