Triple

T9269883
Position Surface form Disambiguated ID Type / Status
Subject Talgo 350 E222797 entity
Predicate alsoKnownAs P39 FINISHED
Object Pato
Pato is the nickname for the Talgo 350, a high-speed Spanish train known for its distinctive duck-bill-shaped nose and use on AVE services.
 E788596 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: Pato | Statement: [Talgo 350, alsoKnownAs, Pato]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Pato
Context triple: [Talgo 350, alsoKnownAs, Pato]
  • A. Pato
    Pato is a Galician musician and educator best known internationally as a virtuoso gaita (Galician bagpipe) player and collaborator with jazz and classical ensembles.
  • B. Pato
    Pato is the stage name of Patrice Wilson, a Nigerian-American music producer and songwriter best known for creating viral pop songs such as Rebecca Black’s “Friday.”
  • C. Pichi
    Pichi is an English-based creole language spoken primarily on the island of Bioko in Equatorial Guinea.
  • D. Polillo
    Polillo is a coastal island municipality in the province of Quezon, Philippines, known for its rich marine biodiversity and relatively remote, rural character.
  • E. Pombo
    Pombo is a component or subdivision associated with the larger entity known as Linares y Pombo.
  • 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: Pato
Triple: [Talgo 350, alsoKnownAs, Pato]
Generated description
Pato is the nickname for the Talgo 350, a high-speed Spanish train known for its distinctive duck-bill-shaped nose and use on AVE services.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Pato
Target entity description: Pato is the nickname for the Talgo 350, a high-speed Spanish train known for its distinctive duck-bill-shaped nose and use on AVE services.
  • A. Pato
    Pato is a Galician musician and educator best known internationally as a virtuoso gaita (Galician bagpipe) player and collaborator with jazz and classical ensembles.
  • B. Pato
    Pato is the stage name of Patrice Wilson, a Nigerian-American music producer and songwriter best known for creating viral pop songs such as Rebecca Black’s “Friday.”
  • C. Pichi
    Pichi is an English-based creole language spoken primarily on the island of Bioko in Equatorial Guinea.
  • D. Polillo
    Polillo is a coastal island municipality in the province of Quezon, Philippines, known for its rich marine biodiversity and relatively remote, rural character.
  • E. Pombo
    Pombo is a component or subdivision associated with the larger entity known as Linares y Pombo.
  • 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_69ca841ffe208190aa7bcffbef2f8379 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd078525308190abfb883123742d3f completed April 1, 2026, 11:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69d09c2239a08190b954c8c57ced8fd2 completed April 4, 2026, 5:05 a.m.
NEDg Description generation batch_69d09cf1f2f48190b53e062c3eb4565d completed April 4, 2026, 5:09 a.m.
NED2 Entity disambiguation (via description) batch_69d09d914d688190af609c4485c746cc completed April 4, 2026, 5:11 a.m.
Created at: March 30, 2026, 7:33 p.m.