Triple

T14638349
Position Surface form Disambiguated ID Type / Status
Subject Free Cities E343661 entity
Predicate member P10 FINISHED
Object Lys E343653 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: Lys | Statement: [Free Cities, member, Lys]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lys
Context triple: [Free Cities, member, Lys]
  • A. Lys
    The Lys is a river in northern France and western Belgium that flows through cities like Ghent and is known for its historical role in trade and the textile industry.
  • B. Lys chosen
    Lys is a wealthy and decadent island city-state in the world of *A Song of Ice and Fire* known for its pleasure houses, skilled courtesans, and distinctive Valyrian-descended population.
  • C. Lys
    Lys is a utopian, technologically advanced city in Arthur C. Clarke’s early science fiction universe, known for its preserved vitality and contrast to Earth’s stagnation.
  • D. Lyss
    Lyss is a Swiss municipality in the canton of Bern, known as a regional transport hub and residential town within the greater Bern area.
  • E. Lis
    Lis is a diminutive form of the given name Lisa, commonly used as a short or affectionate variant.
  • 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_69d822e1a2cc81908e5bb93cf61ce3cc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb4aca6448190adf1042dfbfef716 completed April 14, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdd5d2059081908150b6534aebb32f completed May 8, 2026, 12:23 p.m.
Created at: April 10, 2026, 1:26 a.m.