Triple

T8456194
Position Surface form Disambiguated ID Type / Status
Subject Hum Dekhenge E199924 entity
Predicate titleTranslation P38 FINISHED
Object We Shall See
"We Shall See" is the English title of the iconic Urdu poem "Hum Dekhenge" by Faiz Ahmed Faiz, celebrated as a powerful anthem of resistance and hope.
 E735171 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: We Shall See | Statement: [Hum Dekhenge, titleTranslation, We Shall See]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: We Shall See
Context triple: [Hum Dekhenge, titleTranslation, We Shall See]
  • A. I See Now
    "I See Now" is a track featured on the comedy-rap album "Don't Quit Your Day Job!" by Kanye West.
  • B. Do You See
    "Do You See" is a 1994 hip hop single by West Coast rapper and producer Warren G, known for its smooth G-funk production and reflective lyrics.
  • C. On Sight
    "On Sight" is the abrasive, electronic-influenced opening track from Kanye West's 2013 album *Yeezus*, known for its distorted production and confrontational tone.
  • D. I See You
    "I See You" is the end-credits love theme song from the film *Avatar*, performed by Leona Lewis and composed by James Horner and Simon Franglen.
  • E. What I See
    "What I See" is a photography book by Brooklyn Beckham showcasing his personal images and visual perspective on his life and surroundings.
  • 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: We Shall See
Triple: [Hum Dekhenge, titleTranslation, We Shall See]
Generated description
"We Shall See" is the English title of the iconic Urdu poem "Hum Dekhenge" by Faiz Ahmed Faiz, celebrated as a powerful anthem of resistance and hope.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: We Shall See
Target entity description: "We Shall See" is the English title of the iconic Urdu poem "Hum Dekhenge" by Faiz Ahmed Faiz, celebrated as a powerful anthem of resistance and hope.
  • A. I See Now
    "I See Now" is a track featured on the comedy-rap album "Don't Quit Your Day Job!" by Kanye West.
  • B. Do You See
    "Do You See" is a 1994 hip hop single by West Coast rapper and producer Warren G, known for its smooth G-funk production and reflective lyrics.
  • C. On Sight
    "On Sight" is the abrasive, electronic-influenced opening track from Kanye West's 2013 album *Yeezus*, known for its distorted production and confrontational tone.
  • D. I See You
    "I See You" is the end-credits love theme song from the film *Avatar*, performed by Leona Lewis and composed by James Horner and Simon Franglen.
  • E. What I See
    "What I See" is a photography book by Brooklyn Beckham showcasing his personal images and visual perspective on his life and surroundings.
  • 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_69ca8318231881908fd1bc1c4d45d286 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe48e0ae481908b40f7f124b0551e completed March 31, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce1de232508190803fd2dad21e677f completed April 2, 2026, 7:42 a.m.
NEDg Description generation batch_69ce1f88d404819096c6024c0e61d1ea completed April 2, 2026, 7:49 a.m.
NED2 Entity disambiguation (via description) batch_69ce209338b48190ba8375200a5529bd completed April 2, 2026, 7:53 a.m.
Created at: March 30, 2026, 6:10 p.m.