Triple

T5625376
Position Surface form Disambiguated ID Type / Status
Subject Egyptian special forces E147704 entity
Predicate notableUnit P304 FINISHED
Object Unit 777 E27207 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: Unit 777 | Statement: [Egyptian special forces, notableUnit, Unit 777]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Unit 777
Context triple: [Egyptian special forces, notableUnit, Unit 777]
  • A. Unit 777 chosen
    Unit 777 is an elite Egyptian special forces counter-terrorism unit known for high-risk hostage rescue and anti-terror operations.
  • B. Unit 999
    Unit 999 is an elite Egyptian special forces unit known for conducting high-risk counterterrorism, reconnaissance, and unconventional warfare operations.
  • C. UP-78
    UP-78 is the vehicle registration code assigned to motor vehicles registered in Kanpur, Uttar Pradesh, India.
  • D. Seventh Bureau
    The Seventh Bureau is a division within the Chinese Communist Party’s United Front Work Department that focuses on managing and influencing religious affairs.
  • E. UNIT
    UNIT is a fictional military intelligence organization in the Doctor Who universe that defends Earth from alien and supernatural threats.
  • 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_69c00906f2a88190a992c66b13d606d4 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c02235b4e48190a529f70605bf47ca completed March 22, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d6180f081908145f8d70ad6434c completed March 22, 2026, 8:13 p.m.
Created at: March 22, 2026, 3:40 p.m.