Triple

T8732680
Position Surface form Disambiguated ID Type / Status
Subject Huasteca Potosina waterfalls E207295 entity
Predicate nearbyTown P3883 FINISHED
Object Tamasopo
Tamasopo is a small town in the Huasteca Potosina region of San Luis Potosí, Mexico, known for its lush landscapes and popular nearby waterfalls and natural swimming areas.
E757180 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: Tamasopo | Statement: [Huasteca Potosina waterfalls, nearbyTown, Tamasopo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tamasopo
Context triple: [Huasteca Potosina waterfalls, nearbyTown, Tamasopo]
  • A. Tanasitolo
    Tanasitolo is a village-level settlement located within Wajo Regency in South Sulawesi, Indonesia.
  • B. Tiwatope
    Tiwatope is the birth name of Tiwa Savage, a prominent Nigerian singer, songwriter, and actress known as the "Queen of Afrobeats."
  • C. Nokuku
    Nokuku is an indigenous Oceanic language spoken by a small community in Vanuatu.
  • D. Marangona
    Marangona is the largest and most famous bell of St Mark's Campanile in Venice, traditionally used to mark the beginning and end of the working day and to signal important civic events.
  • E. Palaonda
    Palaonda is an indoor ice arena in Bolzano, Italy, primarily used for ice hockey and other sporting and entertainment events.
  • 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: Tamasopo
Triple: [Huasteca Potosina waterfalls, nearbyTown, Tamasopo]
Generated description
Tamasopo is a small town in the Huasteca Potosina region of San Luis Potosí, Mexico, known for its lush landscapes and popular nearby waterfalls and natural swimming areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tamasopo
Target entity description: Tamasopo is a small town in the Huasteca Potosina region of San Luis Potosí, Mexico, known for its lush landscapes and popular nearby waterfalls and natural swimming areas.
  • A. Tanasitolo
    Tanasitolo is a village-level settlement located within Wajo Regency in South Sulawesi, Indonesia.
  • B. Tiwatope
    Tiwatope is the birth name of Tiwa Savage, a prominent Nigerian singer, songwriter, and actress known as the "Queen of Afrobeats."
  • C. Nokuku
    Nokuku is an indigenous Oceanic language spoken by a small community in Vanuatu.
  • D. Marangona
    Marangona is the largest and most famous bell of St Mark's Campanile in Venice, traditionally used to mark the beginning and end of the working day and to signal important civic events.
  • E. Palaonda
    Palaonda is an indoor ice arena in Bolzano, Italy, primarily used for ice hockey and other sporting and entertainment events.
  • 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_69ca8358e4008190898471a59b96c301 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d2903b08190a5ef29b6d6ca5f1c completed March 31, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf5174db7881908597d5dc472adde9 completed April 3, 2026, 5:34 a.m.
NEDg Description generation batch_69cf53e98a0081909055aacdb0549824 completed April 3, 2026, 5:45 a.m.
NED2 Entity disambiguation (via description) batch_69cf54de42a08190b1ccef9be3220c9e completed April 3, 2026, 5:49 a.m.
Created at: March 30, 2026, 6:37 p.m.