Triple

T32479332
Position Surface form Disambiguated ID Type / Status
Subject Punto Concordia (disputed designation) E830064 entity
Predicate hasDesignation P974 FINISHED
Object Punto Concordia
Punto Concordia is a coastal landmark at the Peru–Chile border that has been the focus of a long-standing territorial and maritime boundary dispute between the two countries.
E2008025 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: Punto Concordia | Statement: [Punto Concordia (disputed designation), hasDesignation, Punto Concordia]
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: Punto Concordia
Triple: [Punto Concordia (disputed designation), hasDesignation, Punto Concordia]
Generated description
Punto Concordia is a coastal landmark at the Peru–Chile border that has been the focus of a long-standing territorial and maritime boundary dispute between the two countries.

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_69f3491ff3b48190b50a7fa00bb05b1f completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c3949ffc819083f7e336b3872cb5 completed May 3, 2026, 3:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34669dc0c88190aabe62cd4ddfc34a completed June 18, 2026, 9:43 p.m.
NEDg Description generation batch_6a34674302f081908ce094e58ee8360c completed June 18, 2026, 9:46 p.m.
NED2 Entity disambiguation (via description) batch_6a3468279dbc8190b5efcecd6f4aa23c completed June 18, 2026, 9:50 p.m.
Created at: May 1, 2026, 12:58 a.m.