Triple

T5646993
Position Surface form Disambiguated ID Type / Status
Subject Indrajit E124408 entity
Predicate hasSibling P363 FINISHED
Object Atikaya E486050 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: Atikaya | Statement: [Indrajit, hasSibling, Atikaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Atikaya
Context triple: [Indrajit, hasSibling, Atikaya]
  • A. Atikaya chosen
    Atikaya is a powerful warrior and son of the demon king Ravana in the Hindu epic Ramayana, known for his strength and valor in battle against Rama’s forces.
  • B. Atakule
    Atakule is a prominent observation and communications tower in Ankara, Turkey, known for its panoramic city views and revolving restaurant.
  • C. Handan
    Handan is a notable novel by Turkish author Halide Edib Adıvar that explores themes of love, identity, and the changing role of women in early 20th-century Ottoman society.
  • D. Handan
    Handan is a historic industrial city in southern Hebei Province, China, known as a former capital of the ancient State of Zhao and an important regional transportation and manufacturing hub.
  • E. Kaghan
    Kaghan is a scenic valley in Pakistan’s Khyber Pakhtunkhwa province, renowned for its lush landscapes, rivers, and popular tourist resorts.
  • 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_69c00825df388190a58742fa9b1aa33d completed March 22, 2026, 3:17 p.m.
NER Named-entity recognition batch_69c022abf0108190b10b3a9fe1688bf9 completed March 22, 2026, 5:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d88bbf08190b32d1ad157e28fe4 completed March 22, 2026, 8:14 p.m.
Created at: March 22, 2026, 3:41 p.m.