Triple
T22094393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Om Puri |
E545987
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Gupt
Gupt is a 1997 Indian Hindi-language thriller film best known for its suspenseful plot and memorable twist ending.
|
E1518918
|
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: Gupt | Statement: [Om Puri, notableWork, Gupt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gupt Context triple: [Om Puri, notableWork, Gupt]
-
A.
Gupta
Gupta refers to the ancient Indian royal dynasty that established and ruled the Gupta Empire, a classical age of significant cultural, scientific, and political achievements in South Asia.
-
B.
Purugupta
Purugupta was a Gupta dynasty ruler of northern India in the 5th century CE, known as a successor in the imperial Gupta lineage during its later phase.
-
C.
Das Gupta
Das Gupta is a surname of Indian origin borne by various notable individuals across fields such as politics, arts, and academia.
-
D.
Nahapana
Nahapana was a prominent early 2nd-century CE Indo-Scythian ruler of western India, known for his extensive coinage and conflicts with the Satavahana dynasty.
-
E.
Gupta Rajan
Gupta Rajan is a quirky, loyal airport janitor in the film "The Terminal" who befriends Viktor Navorski and provides both comic relief and emotional support.
- 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: Gupt Triple: [Om Puri, notableWork, Gupt]
Generated description
Gupt is a 1997 Indian Hindi-language thriller film best known for its suspenseful plot and memorable twist ending.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gupt Target entity description: Gupt is a 1997 Indian Hindi-language thriller film best known for its suspenseful plot and memorable twist ending.
-
A.
Gupta
Gupta refers to the ancient Indian royal dynasty that established and ruled the Gupta Empire, a classical age of significant cultural, scientific, and political achievements in South Asia.
-
B.
Purugupta
Purugupta was a Gupta dynasty ruler of northern India in the 5th century CE, known as a successor in the imperial Gupta lineage during its later phase.
-
C.
Das Gupta
Das Gupta is a surname of Indian origin borne by various notable individuals across fields such as politics, arts, and academia.
-
D.
Nahapana
Nahapana was a prominent early 2nd-century CE Indo-Scythian ruler of western India, known for his extensive coinage and conflicts with the Satavahana dynasty.
-
E.
Gupta Rajan
Gupta Rajan is a quirky, loyal airport janitor in the film "The Terminal" who befriends Viktor Navorski and provides both comic relief and emotional support.
- 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128e766388190aad1039fe0849771 |
completed | April 28, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a879f826881909cdad0edc6bde08d |
completed | May 18, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_6a0a884eb8248190b98b260d3d277d92 |
completed | May 18, 2026, 3:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a8901941c8190945a96d7f5578362 |
completed | May 18, 2026, 3:35 a.m. |
Created at: April 16, 2026, 8:29 p.m.