Triple
T11792417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pankaj Kapur |
E280419
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Sehar
Sehar is a 2005 Indian crime drama film acclaimed for its realistic portrayal of the Uttar Pradesh police force and the criminal underworld.
|
E946894
|
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: Sehar | Statement: [Pankaj Kapur, notableWork, Sehar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sehar Context triple: [Pankaj Kapur, notableWork, Sehar]
-
A.
Barshaini
Barshaini is a small Himalayan village in Himachal Pradesh, India, that serves as a popular base and trailhead for treks into the Parvati Valley and surrounding high-altitude landscapes.
-
B.
Shabara
Shabara was an early Indian philosopher and commentator best known for his influential exegesis on the Purva Mimamsa school of Hindu philosophy.
-
C.
Sharya
Sharya is a town in Kostroma Oblast, Russia, known as a regional railway junction and logging center.
-
D.
Shimsha
Shimsha is a river in southern India that flows through Karnataka and is known for its waterfalls and contribution to the Kaveri river system.
-
E.
Shalim
Shalim is a deity from ancient Canaanite religion, commonly associated with dusk or the setting sun.
- 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: Sehar Triple: [Pankaj Kapur, notableWork, Sehar]
Generated description
Sehar is a 2005 Indian crime drama film acclaimed for its realistic portrayal of the Uttar Pradesh police force and the criminal underworld.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sehar Target entity description: Sehar is a 2005 Indian crime drama film acclaimed for its realistic portrayal of the Uttar Pradesh police force and the criminal underworld.
-
A.
Barshaini
Barshaini is a small Himalayan village in Himachal Pradesh, India, that serves as a popular base and trailhead for treks into the Parvati Valley and surrounding high-altitude landscapes.
-
B.
Shabara
Shabara was an early Indian philosopher and commentator best known for his influential exegesis on the Purva Mimamsa school of Hindu philosophy.
-
C.
Sharya
Sharya is a town in Kostroma Oblast, Russia, known as a regional railway junction and logging center.
-
D.
Shimsha
Shimsha is a river in southern India that flows through Karnataka and is known for its waterfalls and contribution to the Kaveri river system.
-
E.
Shalim
Shalim is a deity from ancient Canaanite religion, commonly associated with dusk or the setting sun.
- 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_69d6ab258b808190b1735835c841e3a4 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a588d2c881909783c2d678c2a474 |
completed | April 10, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f09107fd2481908d765d2188035012 |
completed | April 28, 2026, 10:50 a.m. |
| NEDg | Description generation | batch_69f0bd40108c8190863a60cf01cc7201 |
completed | April 28, 2026, 1:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f0ef7e9f388190b33f6c16abadfde9 |
completed | April 28, 2026, 5:33 p.m. |
Created at: April 8, 2026, 9:42 p.m.