Triple

T26845557
Position Surface form Disambiguated ID Type / Status
Subject Aratoca E675906 entity
Predicate administrativeDivisionOf P747 FINISHED
Object Municipality of Aratoca
The Municipality of Aratoca is a local governmental jurisdiction in Colombia responsible for administering the town of Aratoca and its surrounding rural areas.
E1745499 NE FINISHED

How this triple was built (2 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: Municipality of Aratoca | Statement: [Aratoca, administrativeDivisionOf, Municipality of Aratoca]
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: Municipality of Aratoca
Triple: [Aratoca, administrativeDivisionOf, Municipality of Aratoca]
Generated description
The Municipality of Aratoca is a local governmental jurisdiction in Colombia responsible for administering the town of Aratoca and its surrounding rural areas.

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_69eee9b8d5e88190a07d3455c0fbb21f completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61b4c7e008190825143ff32948abe completed May 2, 2026, 3:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12134d92fc819093c3d5f70ad58c02 completed May 23, 2026, 8:51 p.m.
NEDg Description generation batch_6a12174653308190a7a80b89f4597108 completed May 23, 2026, 9:08 p.m.
NED2 Entity disambiguation (via description) batch_6a1218089b448190bcdd5f2fd5bf0a94 completed May 23, 2026, 9:11 p.m.
Created at: April 27, 2026, 5:11 a.m.