Triple

T2884853
Position Surface form Disambiguated ID Type / Status
Subject First Lady E59480 entity
Predicate usedInCountry P715 FINISHED
Object Lebanon E10701 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: Lebanon | Statement: [First Lady, usedInCountry, Lebanon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lebanon
Context triple: [First Lady, usedInCountry, Lebanon]
  • A. Lebanon chosen
    Lebanon is a small Middle Eastern country on the eastern shore of the Mediterranean Sea, known for its rich history, diverse religious and cultural heritage, and historic capital, Beirut.
  • B. Tunisia
    Tunisia is a North African country on the Mediterranean coast, known for its strategic location, ancient Carthaginian and Roman heritage, and role as a key battleground in World War II.
  • C. Nabatieh, Lebanon
    Nabatieh is a predominantly Shia Muslim city in southern Lebanon known as a regional political and commercial center and for its major Ashura commemorations.
  • D. Circle of Lebanon
    Circle of Lebanon is a distinctive ring of Victorian-era catacombs built around a historic cedar tree in Highgate Cemetery in London.
  • E. Syria
    Syria is a country in the Eastern Mediterranean region of Western Asia, known for its ancient civilizations, diverse cultural heritage, and protracted civil war since 2011.
  • 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_69ab4ac739188190a112f42a5a69c951 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abe04476588190b0db0880e14c79b5 completed March 7, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0316c4fa481909cd5b26ec346d885 completed March 10, 2026, 2:57 p.m.
Created at: March 6, 2026, 10:03 p.m.