Triple

T3402160
Position Surface form Disambiguated ID Type / Status
Subject Paros E71680 entity
Predicate largestTown P235 FINISHED
Object Parikia E356063 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: Parikia | Statement: [Paros, largestTown, Parikia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Parikia
Context triple: [Paros, largestTown, Parikia]
  • A. Parikia chosen
    Parikia is the main port town and administrative center of the Greek island of Paros, known for its traditional Cycladic architecture and historic sites.
  • B. Nusa Kode
    Nusa Kode is a small, remote island within Indonesia’s Komodo archipelago, known for its rugged terrain, rich marine life, and populations of Komodo dragons.
  • C. Bantia
    Bantia was an ancient Oscan-speaking city in southern Italy, notable for yielding important inscriptions that illuminate the Oscan language and Italic legal traditions.
  • D. Sasak
    Sasak is an Austronesian language spoken primarily by the Sasak people on the Indonesian island of Lombok.
  • E. Padang Dinka
    Padang Dinka is a major dialect of the Dinka language spoken primarily by the Padang subgroup of the Dinka people in South Sudan.
  • 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_69ad85aac4808190a092c9cc8911f584 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb8c96d7c8190a1f9d035996f79e3 completed March 8, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69b35466945c8190b01aa016608415a0 completed March 13, 2026, 12:03 a.m.
Created at: March 8, 2026, 3:14 p.m.