Triple

T12461009
Position Surface form Disambiguated ID Type / Status
Subject I Came By E297791 entity
Predicate writer P1360 FINISHED
Object Namsi Khan
Namsi Khan is a screenwriter known for her work on the British thriller film "I Came By."
E984537 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: Namsi Khan | Statement: [I Came By, writer, Namsi Khan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Namsi Khan
Context triple: [I Came By, writer, Namsi Khan]
  • A. Milini Khan
    Milini Khan is an American singer and the daughter of renowned R&B and funk vocalist Chaka Khan.
  • B. Moin Khan
    Moin Khan is a former Pakistani wicketkeeper-batsman and World Cup–winning cricketer who later became a prominent coach and selector for Pakistan cricket.
  • C. Haqq-Nazar Khan
    Haqq-Nazar Khan was a prominent 16th-century ruler who significantly strengthened and expanded the Kazakh Khanate, consolidating its political power on the Central Asian steppe.
  • D. Omar Khan
    Omar Khan was a prominent 19th-century ruler of the Kokand Khanate in Central Asia, known for his patronage of culture and literature.
  • E. Khudayar Khan
    Khudayar Khan was a 19th-century ruler of the Kokand Khanate in Central Asia, known for his turbulent reign marked by internal strife and increasing Russian influence in the region.
  • 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: Namsi Khan
Triple: [I Came By, writer, Namsi Khan]
Generated description
Namsi Khan is a screenwriter known for her work on the British thriller film "I Came By."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Namsi Khan
Target entity description: Namsi Khan is a screenwriter known for her work on the British thriller film "I Came By."
  • A. Milini Khan
    Milini Khan is an American singer and the daughter of renowned R&B and funk vocalist Chaka Khan.
  • B. Moin Khan
    Moin Khan is a former Pakistani wicketkeeper-batsman and World Cup–winning cricketer who later became a prominent coach and selector for Pakistan cricket.
  • C. Haqq-Nazar Khan
    Haqq-Nazar Khan was a prominent 16th-century ruler who significantly strengthened and expanded the Kazakh Khanate, consolidating its political power on the Central Asian steppe.
  • D. Omar Khan
    Omar Khan was a prominent 19th-century ruler of the Kokand Khanate in Central Asia, known for his patronage of culture and literature.
  • E. Khudayar Khan
    Khudayar Khan was a 19th-century ruler of the Kokand Khanate in Central Asia, known for his turbulent reign marked by internal strife and increasing Russian influence in the region.
  • 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_69d6ada270808190b1a2b2e7b02bb426 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94db465c48190bcfaf22f25ef8947 completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f1d4f248190a0805e17da42eaf7 completed May 2, 2026, 6:14 p.m.
NEDg Description generation batch_69f64010a1348190afaf7b95b8f146b5 completed May 2, 2026, 6:18 p.m.
NED2 Entity disambiguation (via description) batch_69f640c33d948190ad8f9885f90786d7 completed May 2, 2026, 6:21 p.m.
Created at: April 8, 2026, 9:56 p.m.