Triple

T18048693
Position Surface form Disambiguated ID Type / Status
Subject México En La Piel E431868 entity
Predicate containsSong P20452 FINISHED
Object La bikina
"La Bikina" is a famous Mexican mariachi song, widely popularized by Luis Miguel and recognized as a classic of traditional Mexican music.
E1302867 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: La bikina | Statement: [México En La Piel, containsSong, La bikina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La bikina
Context triple: [México En La Piel, containsSong, La bikina]
  • A. Birnin Kebbi
    Birnin Kebbi is a city in northwestern Nigeria that serves as the administrative and economic center of Kebbi State.
  • B. Bikenibeu Paeniu
    Bikenibeu Paeniu is a Tuvaluan politician who served multiple terms as the country's prime minister during the 1990s.
  • C. Bindabasini
    Bindabasini is a town located within Nepal's Madhesh Province.
  • D. Bibilis
    Bibilis was an important ancient urban center in Celtiberia, likely serving as a key political and economic hub in the region.
  • E. Cô Bé
    Cô Bé is a youthful female spirit in the Vietnamese Đạo Mẫu tradition, often revered as a playful yet protective attendant of higher mother goddesses.
  • 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: La bikina
Triple: [México En La Piel, containsSong, La bikina]
Generated description
"La Bikina" is a famous Mexican mariachi song, widely popularized by Luis Miguel and recognized as a classic of traditional Mexican music.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: La bikina
Target entity description: "La Bikina" is a famous Mexican mariachi song, widely popularized by Luis Miguel and recognized as a classic of traditional Mexican music.
  • A. Birnin Kebbi
    Birnin Kebbi is a city in northwestern Nigeria that serves as the administrative and economic center of Kebbi State.
  • B. Bikenibeu Paeniu
    Bikenibeu Paeniu is a Tuvaluan politician who served multiple terms as the country's prime minister during the 1990s.
  • C. Bindabasini
    Bindabasini is a town located within Nepal's Madhesh Province.
  • D. Bibilis
    Bibilis was an important ancient urban center in Celtiberia, likely serving as a key political and economic hub in the region.
  • E. Cô Bé
    Cô Bé is a youthful female spirit in the Vietnamese Đạo Mẫu tradition, often revered as a playful yet protective attendant of higher mother goddesses.
  • 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_69d8b906482481908183315b9ecf9994 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4bff39394819080407e1614bd5da9 completed April 19, 2026, 11:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0349bd7b288190b6b5f2548379d280 completed May 12, 2026, 3:39 p.m.
NEDg Description generation batch_6a034b81d3a4819087f9ead00f13635e completed May 12, 2026, 3:47 p.m.
NED2 Entity disambiguation (via description) batch_6a034c190a58819096c77a2254511256 completed May 12, 2026, 3:49 p.m.
Created at: April 10, 2026, 10:25 a.m.