Triple

T4884237
Position Surface form Disambiguated ID Type / Status
Subject Southern Lebanon E109401 entity
Predicate contains P35 FINISHED
Object Marjayoun District E477618 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: Marjayoun District | Statement: [Southern Lebanon, contains, Marjayoun District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marjayoun District
Context triple: [Southern Lebanon, contains, Marjayoun District]
  • A. Salhiya district
    Salhiya district is a central neighborhood in Kuwait City known for its commercial complexes, offices, and residential areas.
  • B. Miniyeh-Danniyeh District
    Miniyeh-Danniyeh District is an administrative district in northern Lebanon known for its rural landscape, mountainous terrain, and scattered villages.
  • C. Sidon District
    Sidon District is an administrative district in southern Lebanon that encompasses the coastal city of Sidon and its surrounding areas.
  • D. Hasbaya District chosen
    Hasbaya District is an administrative district in southern Lebanon known for its mountainous landscape, historic town of Hasbaya, and proximity to the Golan Heights and the Israeli border.
  • E. Batroun District
    Batroun District is an administrative district in northern Lebanon known for its coastal towns, historic sites, and wine-producing villages.
  • 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_69bd440f71348190b99938e59fb7f9a1 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6de253ac8190b1112da6953fa4f2 completed March 20, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6fbba1688190a812cac53992dece completed March 21, 2026, 10:15 a.m.
Created at: March 20, 2026, 1:27 p.m.