Triple

T13124500
Position Surface form Disambiguated ID Type / Status
Subject Teenek de la Huasteca E311809 entity
Predicate hasDialect P4251 FINISHED
Object Hidalgo Teenek
Hidalgo Teenek is a regional variety of the Teenek (Huastec) Mayan language spoken in the Mexican state of Hidalgo.
 E1022493 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: Hidalgo Teenek | Statement: [Teenek de la Huasteca, hasDialect, Hidalgo Teenek]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hidalgo Teenek
Context triple: [Teenek de la Huasteca, hasDialect, Hidalgo Teenek]
  • A. Blanquillos
    Blanquillos is a popular nickname for the Spanish football club Real Zaragoza, referring to the team’s traditional white kit.
  • B. Hidalgo
    Hidalgo is a central Mexican state known for its mountainous terrain, rich mining history, and diverse indigenous cultural heritage.
  • C. Hidalgo
    Hidalgo is a major Mexico City Metro station that serves as an important transfer point between multiple lines in the city’s rapid transit system.
  • D. Hidalgo
    Hidalgo is a 2004 adventure Western film starring Viggo Mortensen as a long-distance rider competing in a grueling desert horse race.
  • E. Hidalgo
    Hidalgo is a common Spanish surname historically associated with minor nobility and widely borne across the Spanish-speaking world.
  • 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: Hidalgo Teenek
Triple: [Teenek de la Huasteca, hasDialect, Hidalgo Teenek]
Generated description
Hidalgo Teenek is a regional variety of the Teenek (Huastec) Mayan language spoken in the Mexican state of Hidalgo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hidalgo Teenek
Target entity description: Hidalgo Teenek is a regional variety of the Teenek (Huastec) Mayan language spoken in the Mexican state of Hidalgo.
  • A. Blanquillos
    Blanquillos is a popular nickname for the Spanish football club Real Zaragoza, referring to the team’s traditional white kit.
  • B. Hidalgo
    Hidalgo is a central Mexican state known for its mountainous terrain, rich mining history, and diverse indigenous cultural heritage.
  • C. Hidalgo
    Hidalgo is a common Spanish surname historically associated with minor nobility and widely borne across the Spanish-speaking world.
  • D. Hidalgo
    Hidalgo is a major Mexico City Metro station that serves as an important transfer point between multiple lines in the city’s rapid transit system.
  • E. Hidalgo
    Hidalgo is a 2004 adventure Western film starring Viggo Mortensen as a long-distance rider competing in a grueling desert horse race.
  • 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_69d806a9fe888190b081e2d9ea665d6c completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9819946808190b41335fb1054accd completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e289462c8190b1625a26f019d744 completed May 3, 2026, 5:52 a.m.
NEDg Description generation batch_69f6e44fa8c88190a8f7bd715f34ec0b completed May 3, 2026, 5:59 a.m.
NED2 Entity disambiguation (via description) batch_69f6e4c96b8c8190bb2f2988a5f8a14b completed May 3, 2026, 6:01 a.m.
Created at: April 9, 2026, 9:07 p.m.