Triple

T15228760
Position Surface form Disambiguated ID Type / Status
Subject Silang E363943 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Amadeo E364959 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: Amadeo | Statement: [Silang, neighboringMunicipality, Amadeo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amadeo
Context triple: [Silang, neighboringMunicipality, Amadeo]
  • A. Amadeo chosen
    Amadeo is a small agricultural municipality in the province of Cavite in the Philippines, known particularly for its coffee production.
  • B. Amedeo
    Amedeo is an Italian given name most famously borne by the scientist Amedeo Avogadro, known for Avogadro's law and Avogadro's number in chemistry.
  • C. Eugenio
    Eugenio is a masculine given name of Greek origin, commonly used in Spanish- and Italian-speaking countries.
  • D. Ambrogio
    Ambrogio is an Italian given name, historically borne by notable figures such as generals, artists, and saints.
  • E. Silvano
    Silvano is an Italian given name, related to Silvio, traditionally associated with the Latin name Silvanus meaning "of the forest" or "woodland."
  • 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_69d85a0ce24c81909c4d3b6475548c95 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0078ccdf48190b34eabd9e24e45a1 completed April 15, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fee5edca5c8190827788324a9e886d completed May 9, 2026, 7:44 a.m.
Created at: April 10, 2026, 3:12 a.m.