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.