Triple
T11102673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raj Kapoor |
E262550
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Andaz
Andaz is a classic 1949 Hindi romantic drama film, directed by Mehboob Khan and starring Raj Kapoor, Nargis, and Dilip Kumar, known for its love triangle and progressive themes.
|
E904733
|
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: Andaz | Statement: [Raj Kapoor, notableWork, Andaz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andaz Context triple: [Raj Kapoor, notableWork, Andaz]
-
A.
Andaz
Andaz is a luxury boutique hotel brand known for its contemporary design, locally inspired experiences, and personalized service.
-
B.
Rangbaaz
Rangbaaz is a Bangladeshi film that helped establish actor Razzak as a major star in the country’s cinema.
-
C.
Andaandi
Andaandi is a Nubian language variety spoken primarily in the Dongola region of northern Sudan.
-
D.
Ghum
Ghum is a small hill station in West Bengal, India, known for its high-altitude railway station on the Darjeeling Himalayan Railway and its scenic views of the surrounding Himalayas.
-
E.
Andhadhun
Andhadhun is a critically acclaimed 2018 Indian black comedy thriller film directed by Sriram Raghavan, known for its twist-filled plot and standout performances.
- 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: Andaz Triple: [Raj Kapoor, notableWork, Andaz]
Generated description
Andaz is a classic 1949 Hindi romantic drama film, directed by Mehboob Khan and starring Raj Kapoor, Nargis, and Dilip Kumar, known for its love triangle and progressive themes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Andaz Target entity description: Andaz is a classic 1949 Hindi romantic drama film, directed by Mehboob Khan and starring Raj Kapoor, Nargis, and Dilip Kumar, known for its love triangle and progressive themes.
-
A.
Andaz
Andaz is a luxury boutique hotel brand known for its contemporary design, locally inspired experiences, and personalized service.
-
B.
Rangbaaz
Rangbaaz is a Bangladeshi film that helped establish actor Razzak as a major star in the country’s cinema.
-
C.
Andaandi
Andaandi is a Nubian language variety spoken primarily in the Dongola region of northern Sudan.
-
D.
Ghum
Ghum is a small hill station in West Bengal, India, known for its high-altitude railway station on the Darjeeling Himalayan Railway and its scenic views of the surrounding Himalayas.
-
E.
Andhadhun
Andhadhun is a critically acclaimed 2018 Indian black comedy thriller film directed by Sriram Raghavan, known for its twist-filled plot and standout performances.
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79a2c30a481908c45020c37caebe4 |
completed | April 9, 2026, 12:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3e7f9b46881909761ed448fa5ce6e |
completed | April 18, 2026, 8:22 p.m. |
| NEDg | Description generation | batch_69e3f2cc9b7c8190bb5fd89f239917cf |
completed | April 18, 2026, 9:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e3f4a37b6c81908ca63270d82579ae |
completed | April 18, 2026, 9:16 p.m. |
Created at: April 8, 2026, 9:27 p.m.