Triple

T4527215
Position Surface form Disambiguated ID Type / Status
Subject Logudoro E106207 entity
Predicate contains P35 FINISHED
Object Tergu E423879 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: Tergu | Statement: [Logudoro, contains, Tergu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tergu
Context triple: [Logudoro, contains, Tergu]
  • A. Tergu chosen
    Tergu is a small municipality in the Gallura region of northern Sardinia, Italy, known for its rural setting and historic Romanesque church of Nostra Signora di Tergu.
  • B. Teron
    Teron is one of the traditional clans of the Karbi people, an indigenous ethnic group primarily inhabiting the Karbi Anglong region of Assam in Northeast India.
  • C. The Turim
    The Turim is a foundational 14th-century Jewish legal code by Rabbi Jacob ben Asher that systematically organizes halakhic rulings into four major sections.
  • D. Teroenza
    Teroenza is a character in the Star Wars universe known for being one of the earlier owners of the iconic starship Millennium Falcon.
  • E. Tura
    Tura is a district in southern Cairo, Egypt, historically known for its limestone quarries used in ancient Egyptian monuments.
  • 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_69bd43f3d6e08190a91824f833d51bbe completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd577737848190ad509c8bb8e57ec0 completed March 20, 2026, 2:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69bda4577d0c8190a88cdf4523446329 completed March 20, 2026, 7:47 p.m.
Created at: March 20, 2026, 1:03 p.m.