Triple
T8503850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Javed Akhtar |
E201285
|
entity |
| Predicate | wroteScreenplayFor |
P15305
|
FINISHED |
| Object |
Don
Don is a classic 1978 Bollywood action-thriller film, starring Amitabh Bachchan in a dual role, that became iconic for its stylish crime narrative, memorable music, and enduring cultural impact.
|
E739212
|
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: Don | Statement: [Javed Akhtar, wroteScreenplayFor, Don]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Don Context triple: [Javed Akhtar, wroteScreenplayFor, Don]
-
A.
Don
The Don is a major river in southwestern Russia that flows from the Central Russian Upland to the Sea of Azov, historically serving as an important trade route and cultural boundary.
-
B.
Don
Don is a masculine given name, often a short form of Donald, used in English-speaking countries.
-
C.
Danny
Danny is a masculine given name, often used as a diminutive of Daniel.
-
D.
Danny
Danny is the young boy protagonist of the science-fiction adventure film "Zathura: A Space Adventure," whose discovery of a mysterious board game launches the story’s intergalactic journey.
-
E.
Danny
Danny is a supporting character in Woody Allen's 2013 drama film "Blue Jasmine," involved in the personal and emotional turmoil surrounding the protagonist's life.
- 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: Don Triple: [Javed Akhtar, wroteScreenplayFor, Don]
Generated description
Don is a classic 1978 Bollywood action-thriller film, starring Amitabh Bachchan in a dual role, that became iconic for its stylish crime narrative, memorable music, and enduring cultural impact.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Don Target entity description: Don is a classic 1978 Bollywood action-thriller film, starring Amitabh Bachchan in a dual role, that became iconic for its stylish crime narrative, memorable music, and enduring cultural impact.
-
A.
Don
The Don is a major river in southwestern Russia that flows from the Central Russian Upland to the Sea of Azov, historically serving as an important trade route and cultural boundary.
-
B.
Don
Don is a masculine given name, often a short form of Donald, used in English-speaking countries.
-
C.
Danny
Danny is the young boy protagonist of the science-fiction adventure film "Zathura: A Space Adventure," whose discovery of a mysterious board game launches the story’s intergalactic journey.
-
D.
Danny
Danny is a masculine given name, often used as a diminutive of Daniel.
-
E.
Danny
Danny is the young, psychically gifted son of Jack Torrance in Stephen King’s horror novel "The Shining" and its film adaptations.
- 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_69ca831fe47c8190b5c57b456d2aefa0 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe59d67d081908155a43b9b463fe3 |
completed | March 31, 2026, 3:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce4e26a3108190a48b00c2927be971 |
completed | April 2, 2026, 11:08 a.m. |
| NEDg | Description generation | batch_69ce4ff88ff48190a5641635187a9e4f |
completed | April 2, 2026, 11:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce50fd3150819097562093bee78a6d |
completed | April 2, 2026, 11:20 a.m. |
Created at: March 30, 2026, 6:14 p.m.