Triple

T9803086
Position Surface form Disambiguated ID Type / Status
Subject Bayda E237887 entity
Predicate alternativeName P39 FINISHED
Object Al Bayda E99697 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: Al Bayda | Statement: [Bayda, alternativeName, Al Bayda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Al Bayda
Context triple: [Bayda, alternativeName, Al Bayda]
  • A. Al Bayda chosen
    Al Bayda is a city in northeastern Libya that serves as one of the main urban centers of the Cyrenaica region.
  • B. Misrata
    Misrata is a key coastal city in northwestern Libya, known as an important commercial and industrial hub and a strategic port on the Mediterranean Sea.
  • C. Djimla
    Djimla is a small town and commune located in northeastern Algeria within the coastal and mountainous region of Jijel Province.
  • D. Al Bayda Governorate
    Al Bayda Governorate is a central Yemeni administrative region known for its rugged terrain and ongoing armed conflict involving various militant and government forces.
  • E. Hamina
    Hamina is a coastal town and municipality in southeastern Finland known for its historic star-shaped fortress and strategic location on the Gulf of Finland.
  • 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_69ca84dd4608819097ff4ed00feca280 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdab78832481909b184b21a8a46e50 completed April 1, 2026, 11:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1d5aecdec81909fae349945406c6c completed April 5, 2026, 3:23 a.m.
Created at: March 30, 2026, 8:29 p.m.