Triple

T16183247
Position Surface form Disambiguated ID Type / Status
Subject Mohammed Aamir Hussain Khan E392736 entity
Predicate notableWork P4 FINISHED
Object PK
PK is a 2014 Indian satirical science fiction comedy film directed by Rajkumar Hirani, known for its critique of religious dogma and superstition through the story of an alien played by Aamir Khan.
E1199367 NE FINISHED

How this triple was built (4 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: PK | Statement: [Mohammed Aamir Hussain Khan, notableWork, PK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PK
Context triple: [Mohammed Aamir Hussain Khan, notableWork, PK]
  • A. PK
    PK is a compact bitmap font file format traditionally used by TeX systems to store rasterized glyphs generated from METAFONT sources.
  • B. PK
    PK is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Pakistan in international standards and systems.
  • C. PK
    PK is a music producer best known for his work on DMX's influential debut album "It's Dark and Hell Is Hot."
  • D. KP
    KP is a subsystem of axiomatic set theory that omits the power set axiom and focuses on sets that are constructible via definable operations.
  • E. KP
    KP is the commonly used abbreviation for Khyber Pakhtunkhwa, a province in northwestern Pakistan known for its mountainous terrain and diverse ethnic communities.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: PK
Triple: [Mohammed Aamir Hussain Khan, notableWork, PK]
Generated description
PK is a 2014 Indian satirical science fiction comedy film directed by Rajkumar Hirani, known for its critique of religious dogma and superstition through the story of an alien played by Aamir Khan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: PK
Target entity description: PK is a 2014 Indian satirical science fiction comedy film directed by Rajkumar Hirani, known for its critique of religious dogma and superstition through the story of an alien played by Aamir Khan.
  • A. PK
    PK is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Pakistan in international standards and systems.
  • B. PK
    PK is a compact bitmap font file format traditionally used by TeX systems to store rasterized glyphs generated from METAFONT sources.
  • C. PK
    PK is a music producer best known for his work on DMX's influential debut album "It's Dark and Hell Is Hot."
  • D. KP
    KP is the post-nominal abbreviation used by knights of the Order of Saint Patrick, a British order of chivalry associated with Ireland.
  • E. KP
    KP is a subsystem of axiomatic set theory that omits the power set axiom and focuses on sets that are constructible via definable operations.
  • F. None of above. chosen

Provenance (5 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e2205ef39081908da383abdebc2ccc completed April 17, 2026, 11:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffff03400481908e66db8cf0213c15 completed May 10, 2026, 3:44 a.m.
NEDg Description generation batch_6a0000ceba648190ac5ecefd34f10d4e completed May 10, 2026, 3:51 a.m.
NED2 Entity disambiguation (via description) batch_6a00013fdb1c8190add653fc1cf30e44 completed May 10, 2026, 3:53 a.m.
Created at: April 10, 2026, 5:02 a.m.