Triple

T2638221
Position Surface form Disambiguated ID Type / Status
Subject Ica Region E62797 entity
Predicate hasCity P316 FINISHED
Object Palpa E61192 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: Palpa | Statement: [Ica Region, hasCity, Palpa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Palpa
Context triple: [Ica Region, hasCity, Palpa]
  • A. Palpa chosen
    Palpa is a small town in Peru’s Ica Region known as a nearby center for viewing ancient geoglyphs similar to the Nazca Lines.
  • B. Melipal
    Melipal is one of the Unit Telescopes of the Very Large Telescope array at ESO’s Paranal Observatory in Chile, used for advanced optical and infrared astronomical observations.
  • C. Pischa
    Pischa is a mountain area and ski region near Davos in the Swiss Alps, known for its freeride terrain and winter sports opportunities.
  • D. Palas
    Palas is the main residential and ceremonial building within Nuremberg Castle, historically used as the living quarters and audience hall of the ruling nobility.
  • E. Palas
    Palas is a remote valley and settlement in Pakistan’s Kohistan region, known for its rugged terrain, rich biodiversity, and traditional mountain communities.
  • 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_69ab4c3f2dcc819082df80f5e032f690 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abd8e470ac8190bd0d6de6805afcd0 completed March 7, 2026, 7:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69af90b628748190bdbb23f1d85bc3fd completed March 10, 2026, 3:32 a.m.
Created at: March 6, 2026, 9:53 p.m.