Triple

T10481127
Position Surface form Disambiguated ID Type / Status
Subject Sureth E247170 entity
Predicate alternativeName P39 FINISHED
Object Surayt E466789 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: Surayt | Statement: [Sureth, alternativeName, Surayt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Surayt
Context triple: [Sureth, alternativeName, Surayt]
  • A. Surayt chosen
    Surayt is a modern Aramaic language variety traditionally spoken by Syriac Christian communities from the Tur Abdin region in southeastern Turkey and neighboring areas.
  • B. Qurayyat
    Qurayyat is a city in northern Saudi Arabia near the Jordanian border, known as a key transit and trade hub in the Al Jawf region.
  • C. Sumartin
    Sumartin is a coastal village and ferry port on the eastern tip of the Croatian island of Brač, known for its quiet beaches and traditional fishing atmosphere.
  • D. Sassoun
    Sassoun is a mountainous region in historic Western Armenia, famed in Armenian folklore as the homeland of the legendary heroes of the national epic.
  • E. Zarruq
    Zarruq is the honorific title of Ahmad Zarruq, a renowned 15th-century Moroccan Sufi scholar, jurist, and reformer known for integrating Islamic law and Sufism.
  • 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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5095c5dc88190902582db28df01b4 completed April 7, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8dc73991881909aa538fce1e05a7c completed April 10, 2026, 11:18 a.m.
Created at: April 6, 2026, 12:22 p.m.