Triple
T16527842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mani Kaul |
E401485
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Nazar
Nazar is an Indian art-house film directed by acclaimed filmmaker Mani Kaul, known for its experimental narrative style and visual minimalism.
|
E1218710
|
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: Nazar | Statement: [Mani Kaul, notableWork, Nazar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nazar Context triple: [Mani Kaul, notableWork, Nazar]
-
A.
Navakhai
Navakhai is a traditional harvest festival celebrated by agrarian communities, particularly in parts of central and eastern India, to mark the consumption of the season’s newly harvested grain.
-
B.
Zahar
Zahar is the surname of Mahmoud Zahar, a prominent Palestinian co-founder and senior leader of the Hamas movement in Gaza.
-
C.
Nazran
Nazran is a town in the Republic of Ingushetia in southwestern Russia, historically one of the region’s main population centers and transport hubs.
-
D.
Mirzam
Mirzam is a bright blue-white giant star in the constellation Canis Major, known as one of the prominent stars near Sirius in the winter sky.
-
E.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
- 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: Nazar Triple: [Mani Kaul, notableWork, Nazar]
Generated description
Nazar is an Indian art-house film directed by acclaimed filmmaker Mani Kaul, known for its experimental narrative style and visual minimalism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nazar Target entity description: Nazar is an Indian art-house film directed by acclaimed filmmaker Mani Kaul, known for its experimental narrative style and visual minimalism.
-
A.
Navakhai
Navakhai is a traditional harvest festival celebrated by agrarian communities, particularly in parts of central and eastern India, to mark the consumption of the season’s newly harvested grain.
-
B.
Zahar
Zahar is the surname of Mahmoud Zahar, a prominent Palestinian co-founder and senior leader of the Hamas movement in Gaza.
-
C.
Nazran
Nazran is a town in the Republic of Ingushetia in southwestern Russia, historically one of the region’s main population centers and transport hubs.
-
D.
Mirzam
Mirzam is a bright blue-white giant star in the constellation Canis Major, known as one of the prominent stars near Sirius in the winter sky.
-
E.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32ed57be481908625d4c5aab0940c |
completed | April 18, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00608efd0c81908e64419bd74eb285 |
completed | May 10, 2026, 10:40 a.m. |
| NEDg | Description generation | batch_6a0062cbe9048190823db47a42dac26a |
completed | May 10, 2026, 10:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00635f57c08190ad915082b00b0f88 |
completed | May 10, 2026, 10:52 a.m. |
Created at: April 10, 2026, 5:14 a.m.