Triple
T22858995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vyjayanthimala |
E566858
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Sunghursh
Sunghursh is a 1968 Hindi-language period drama film, noted for its ensemble cast and acclaimed performance by leading actress Vyjayanthimala.
|
E1558176
|
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: Sunghursh | Statement: [Vyjayanthimala, notableWork, Sunghursh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sunghursh Context triple: [Vyjayanthimala, notableWork, Sunghursh]
-
A.
Akurgal
Akurgal is a Turkish surname most notably associated with the prominent archaeologist Ekrem Akurgal.
-
B.
Shenir
Shenir is an alternate name for the Sinyar language, a Nilo-Saharan language spoken by the Sinyar people of western Sudan and eastern Chad.
-
C.
Gosamyr
Gosamyr is a lesser-known Marvel Comics character, an alien with emotion-amplifying powers who briefly allied with the New Mutants.
-
D.
Mongul
Mongul is a powerful and ruthless intergalactic warlord in DC Comics, often depicted as a major adversary of Superman and the Green Lantern Corps.
-
E.
Ye-Maek
Ye-Maek was an ancient tribal group of northeastern Korea and Manchuria believed to be ancestral to or closely related with early Korean kingdoms such as Goguryeo and Buyeo.
- 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: Sunghursh Triple: [Vyjayanthimala, notableWork, Sunghursh]
Generated description
Sunghursh is a 1968 Hindi-language period drama film, noted for its ensemble cast and acclaimed performance by leading actress Vyjayanthimala.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sunghursh Target entity description: Sunghursh is a 1968 Hindi-language period drama film, noted for its ensemble cast and acclaimed performance by leading actress Vyjayanthimala.
-
A.
Akurgal
Akurgal is a Turkish surname most notably associated with the prominent archaeologist Ekrem Akurgal.
-
B.
Shenir
Shenir is an alternate name for the Sinyar language, a Nilo-Saharan language spoken by the Sinyar people of western Sudan and eastern Chad.
-
C.
Gosamyr
Gosamyr is a lesser-known Marvel Comics character, an alien with emotion-amplifying powers who briefly allied with the New Mutants.
-
D.
Mongul
Mongul is a powerful and ruthless intergalactic warlord in DC Comics, often depicted as a major adversary of Superman and the Green Lantern Corps.
-
E.
Ye-Maek
Ye-Maek was an ancient tribal group of northeastern Korea and Manchuria believed to be ancestral to or closely related with early Korean kingdoms such as Goguryeo and Buyeo.
- 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_69e24589083081908d5694c4fdc80086 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17ebf1838819092b2b99205a2192f |
completed | April 29, 2026, 3:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0bae8ba1dc8190a2af113d88c210d0 |
completed | May 19, 2026, 12:27 a.m. |
| NEDg | Description generation | batch_6a0baf39c42c8190a6401ab150b80039 |
completed | May 19, 2026, 12:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0bafce9cf48190a826f713e095e3be |
completed | May 19, 2026, 12:33 a.m. |
Created at: April 17, 2026, 3:37 p.m.