Triple

T19511268
Position Surface form Disambiguated ID Type / Status
Subject Al-Ashrafiya Mosque E488158 entity
Predicate locatedIn P40 FINISHED
Object Old City of Taiz NE NERFINISHED

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: Old City of Taiz | Statement: [Al-Ashrafiya Mosque, locatedIn, Old City of Taiz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Old City of Taiz
Context triple: [Al-Ashrafiya Mosque, locatedIn, Old City of Taiz]
  • A. old city of Ibb
    The old city of Ibb is a historic Yemeni urban center renowned for its dense traditional architecture, stone tower houses, and rich cultural heritage.
  • B. Zabid
    Zabid is an ancient city in western Yemen renowned as a former political capital and a historic center of Islamic learning and culture.
  • C. Ma'rib
    Ma'rib is an ancient city in present-day Yemen that served as the political and religious center of the Sabaean civilization, renowned for its monumental dam and role in South Arabian trade.
  • D. Taiz chosen
    Taiz is one of Yemen’s largest and historically most important cities, known as a cultural and intellectual center in the country.
  • E. Sanaʽa
    Sanaʽa is the historic capital and one of the largest cities of Yemen, renowned for its ancient architecture and cultural significance in the Arabian Peninsula.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8da8bec819081f400199491ccc3 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63516572c8190a8719c51fd3f7147 completed April 20, 2026, 2:15 p.m.
Created at: April 10, 2026, 1:40 p.m.