Triple

T3712472
Position Surface form Disambiguated ID Type / Status
Subject Ihnasya E81446 entity
Predicate currency P245 FINISHED
Object Egyptian pound E4066 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: Egyptian pound | Statement: [Ihnasya, currency, Egyptian pound]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Egyptian pound
Context triple: [Ihnasya, currency, Egyptian pound]
  • A. Egyptian pound chosen
    The Egyptian pound is the official monetary unit of Egypt, used for everyday transactions, pricing, and financial operations throughout the country.
  • B. Sudanese pound
    The Sudanese pound is the official monetary unit of Sudan, used for everyday transactions and economic activities within the country.
  • C. Palestine pound
    The Palestine pound was the official currency used in the British-administered territory of Palestine during the first half of the 20th century, pegged to and modeled on the British pound sterling.
  • D. Libyan dinar
    The Libyan dinar is the official monetary unit of Libya, used for everyday transactions and economic activities throughout the country.
  • E. Syrian pound
    The Syrian pound is the official monetary unit of Syria, issued by the Central Bank of Syria and subdivided into 100 piastres.
  • 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_69ad8b1a81588190b3f27a5483bb610e completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adc9cbc5648190936f93868086167e completed March 8, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4ce0834288190b16cf49477dc2ed9 completed March 14, 2026, 2:55 a.m.
Created at: March 8, 2026, 3:33 p.m.