Triple

T19735129
Position Surface form Disambiguated ID Type / Status
Subject Cerro Apoquindo foothills E473958 entity
Predicate borders P224 FINISHED
Object city of Santiago E1009466 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: city of Santiago | Statement: [Cerro Apoquindo foothills, borders, city of Santiago]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Santiago
Context triple: [Cerro Apoquindo foothills, borders, city of Santiago]
  • A. City of Santiago
    The City of Santiago is the capital and largest urban center of Chile, serving as the country’s political, economic, and cultural hub.
  • B. city of Santiago, Chile chosen
    The city of Santiago is the capital and largest urban center of Chile, serving as the country’s political, cultural, and economic hub in the central valley near the Andes Mountains.
  • C. Santiago City
    Santiago City is a highly urbanized commercial and industrial center in the Cagayan Valley region of the Philippines.
  • D. Santiago
    Santiago is the capital and primary economic, political, and cultural center of Chile, located in the country’s central valley.
  • E. Santiago
    Santiago is a charismatic bohemian performer and friend of Christian in *Moulin Rouge! The Musical*, contributing comic relief, passion, and artistic flair to the story.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d8e517ebd48190979ee76723bcfadf completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6515d138c8190a4c4d112ed5756a3 completed April 20, 2026, 4:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a07d428853c8190b7df67f52e59ba32 completed May 16, 2026, 2:19 a.m.
Created at: April 10, 2026, 1:47 p.m.