Triple

T11316856
Position Surface form Disambiguated ID Type / Status
Subject Arecibo, Puerto Rico E267989 entity
Predicate hasBarrio P4813 FINISHED
Object Hato Abajo
Hato Abajo is a barrio (district) of the municipality of Arecibo on the northern coast of Puerto Rico.
E919751 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: Hato Abajo | Statement: [Arecibo, Puerto Rico, hasBarrio, Hato Abajo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hato Abajo
Context triple: [Arecibo, Puerto Rico, hasBarrio, Hato Abajo]
  • A. Loíza
    Loíza is a coastal municipality in Puerto Rico known for its rich Afro-Puerto Rican culture, traditional Bomba music and dance, and vibrant religious and folk festivals.
  • B. Hato Corozal
    Hato Corozal is a rural municipality in eastern Colombia known for its cattle ranching and llanero (plains) culture within the Casanare Department.
  • C. Barranquitas
    Barranquitas is a mountainous inland municipality of Puerto Rico known for its cool climate, scenic views, and traditional cultural festivals.
  • D. Montañita
    Montañita is a popular Ecuadorian beach town renowned for its surfing waves, vibrant nightlife, and laid-back backpacker atmosphere.
  • E. El Carmen
    El Carmen is a town in coastal Ecuador known as an agricultural and commercial center within Manabí Province.
  • 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: Hato Abajo
Triple: [Arecibo, Puerto Rico, hasBarrio, Hato Abajo]
Generated description
Hato Abajo is a barrio (district) of the municipality of Arecibo on the northern coast of Puerto Rico.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hato Abajo
Target entity description: Hato Abajo is a barrio (district) of the municipality of Arecibo on the northern coast of Puerto Rico.
  • A. Loíza
    Loíza is a coastal municipality in Puerto Rico known for its rich Afro-Puerto Rican culture, traditional Bomba music and dance, and vibrant religious and folk festivals.
  • B. Hato Corozal
    Hato Corozal is a rural municipality in eastern Colombia known for its cattle ranching and llanero (plains) culture within the Casanare Department.
  • C. Barranquitas
    Barranquitas is a mountainous inland municipality of Puerto Rico known for its cool climate, scenic views, and traditional cultural festivals.
  • D. Montañita
    Montañita is a popular Ecuadorian beach town renowned for its surfing waves, vibrant nightlife, and laid-back backpacker atmosphere.
  • E. El Carmen
    El Carmen is a town in coastal Ecuador known as an agricultural and commercial center within Manabí Province.
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9c3cf748190987838029d9f7fff completed April 9, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69e542f294988190bb456326e4184dcb completed April 19, 2026, 9:02 p.m.
NEDg Description generation batch_69e5474879088190990468d960b26739 completed April 19, 2026, 9:21 p.m.
NED2 Entity disambiguation (via description) batch_69e54eccdd3881908536ee3f9f4ef516 completed April 19, 2026, 9:53 p.m.
Created at: April 8, 2026, 9:32 p.m.