Triple

T6852629
Position Surface form Disambiguated ID Type / Status
Subject Sahnun E158058 entity
Predicate name P16 FINISHED
Object Sahnun E158058 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: Sahnun | Statement: [Sahnun, name, Sahnun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sahnun
Context triple: [Sahnun, name, Sahnun]
  • A. Sahnun chosen
    Sahnun was a prominent 9th-century Islamic jurist from North Africa whose compilation of legal opinions, the Mudawwana, became a foundational text of the Maliki school of Sunni jurisprudence.
  • B. Bawshar
    Bawshar is a district in Muscat, Oman, known as a major urban area that includes important landmarks, commercial centers, and residential neighborhoods.
  • C. Abu Sneineh
    Abu Sneineh is an Arabic family name notably borne by Taysir Abu Sneineh, a Palestinian political figure.
  • D. El Mounib
    El Mounib is a district in Giza, Egypt, known for serving as a major southern transport hub on the Cairo Metro network.
  • E. Djoum
    Djoum is a small town in southern Cameroon known as a local administrative and trading center within the country's South Region.
  • 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_69c6882fae988190864cbba788c5ebb4 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d84fffbc8190943ca7f3f03937e9 completed March 27, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72fd79e508190b00e45f9cceb3e21 completed March 28, 2026, 1:33 a.m.
Created at: March 27, 2026, 2:20 p.m.