Triple

T8617853
Position Surface form Disambiguated ID Type / Status
Subject Córdoba Department E204085 entity
Predicate containsCity P294 FINISHED
Object Tierralta
Tierralta is a municipality and town in northern Colombia’s Córdoba Department, known for its rural setting and proximity to the Paramillo National Natural Park.
 E746727 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: Tierralta | Statement: [Córdoba Department, containsCity, Tierralta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tierralta
Context triple: [Córdoba Department, containsCity, Tierralta]
  • A. Erdek
    Erdek is a coastal town and popular seaside resort in Turkey’s Balıkesir Province, located on the Kapıdağ Peninsula along the Sea of Marmara.
  • B. Tera
    Tera is a West Chadic language spoken primarily in northeastern Nigeria by the Tera people.
  • C. Terra
    Terra is a sustainability-themed character created as one of the official mascots for Expo 2020 Dubai, symbolizing environmental awareness and ecological responsibility.
  • D. Maa
    Maa is a Nilotic language spoken primarily by the Maasai people of Kenya and Tanzania.
  • E. La Terre
    La Terre is a naturalist novel by Émile Zola that portrays the brutal lives, struggles, and moral decay of French peasants in the 19th century countryside.
  • 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: Tierralta
Triple: [Córdoba Department, containsCity, Tierralta]
Generated description
Tierralta is a municipality and town in northern Colombia’s Córdoba Department, known for its rural setting and proximity to the Paramillo National Natural Park.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tierralta
Target entity description: Tierralta is a municipality and town in northern Colombia’s Córdoba Department, known for its rural setting and proximity to the Paramillo National Natural Park.
  • A. Erdek
    Erdek is a coastal town and popular seaside resort in Turkey’s Balıkesir Province, located on the Kapıdağ Peninsula along the Sea of Marmara.
  • B. Tera
    Tera is a West Chadic language spoken primarily in northeastern Nigeria by the Tera people.
  • C. Terra
    Terra is a sustainability-themed character created as one of the official mascots for Expo 2020 Dubai, symbolizing environmental awareness and ecological responsibility.
  • D. Maa
    Maa is a Nilotic language spoken primarily by the Maasai people of Kenya and Tanzania.
  • E. La Terre
    La Terre is a naturalist novel by Émile Zola that portrays the brutal lives, struggles, and moral decay of French peasants in the 19th century countryside.
  • 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_69ca832ceab8819096e4a9f546695079 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc4711c7748190af26ff5a78ef66a2 completed March 31, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69cebbcb910881909088da53c6e31ae3 completed April 2, 2026, 6:56 p.m.
NEDg Description generation batch_69cebcc22d208190801b4ec58614dfcb completed April 2, 2026, 7 p.m.
NED2 Entity disambiguation (via description) batch_69cebdf3f288819088d83165c741d092 completed April 2, 2026, 7:05 p.m.
Created at: March 30, 2026, 6:26 p.m.