Triple

T6144709
Position Surface form Disambiguated ID Type / Status
Subject Lady of Sais E137046 entity
Predicate associatedWithCity P1481 FINISHED
Object Sais E27217 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: Sais | Statement: [Lady of Sais, associatedWithCity, Sais]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sais
Context triple: [Lady of Sais, associatedWithCity, Sais]
  • A. Sais chosen
    Sais was an ancient Egyptian city in the western Nile Delta that served as a significant religious and political center, especially prominent during the 26th (Saite) Dynasty.
  • B. Saisiyat
    The Saisiyat are one of Taiwan’s indigenous Austronesian-speaking peoples, known for their distinctive culture and the legendary Pasta’ay (Dwarf) ritual.
  • C. Saffais
    Saffais is a small commune in the Meurthe-et-Moselle department of northeastern France.
  • D. Saharias
    Saharias are an indigenous tribal community of central India, traditionally known as forest dwellers and laborers with distinct cultural practices and socio-economic challenges.
  • E. Sousel
    Sousel is a municipality in Portugal’s Alentejo region, known for its rural landscape, agricultural activities, and traditional whitewashed architecture.
  • 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_69c008a2c6308190a56519b22d55d083 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05cb645508190aea2d77c9de174ba completed March 22, 2026, 9:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c16ece259c8190b7258859a35ca4fd completed March 23, 2026, 4:48 p.m.
Created at: March 22, 2026, 4:16 p.m.