Triple
T15920652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shankar |
E386083
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object |
Sankar
Sankar is a common Indian given name and surname, often associated with Hindu cultural and religious traditions.
|
E1184096
|
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: Sankar | Statement: [Shankar, hasVariant, Sankar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sankar Context triple: [Shankar, hasVariant, Sankar]
-
A.
Srikanta
Srikanta is a classic Bengali novel by Sarat Chandra Chattopadhyay that explores the emotional and social struggles of its introspective protagonist against the backdrop of early 20th-century Bengal.
-
B.
Surama Ghatak
Surama Ghatak was the wife of renowned Indian filmmaker Ritwik Ghatak and a figure associated with his personal and artistic life.
-
C.
Taraknath
Taraknath is an Indian given name commonly used for males, often associated with Bengali cultural and religious traditions.
-
D.
Nandha
Nandha is a 2001 Tamil-language drama film directed by Bala, widely recognized for Suriya’s breakthrough performance in a gritty, emotionally intense role.
-
E.
Sitarama
Sitarama is a revered epithet of the Hindu deity Rama that emphasizes his inseparable union with his consort Sita and their ideal of divine marital devotion.
- 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: Sankar Triple: [Shankar, hasVariant, Sankar]
Generated description
Sankar is a common Indian given name and surname, often associated with Hindu cultural and religious traditions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sankar Target entity description: Sankar is a common Indian given name and surname, often associated with Hindu cultural and religious traditions.
-
A.
Srikanta
Srikanta is a classic Bengali novel by Sarat Chandra Chattopadhyay that explores the emotional and social struggles of its introspective protagonist against the backdrop of early 20th-century Bengal.
-
B.
Surama Ghatak
Surama Ghatak was the wife of renowned Indian filmmaker Ritwik Ghatak and a figure associated with his personal and artistic life.
-
C.
Taraknath
Taraknath is an Indian given name commonly used for males, often associated with Bengali cultural and religious traditions.
-
D.
Nandha
Nandha is a 2001 Tamil-language drama film directed by Bala, widely recognized for Suriya’s breakthrough performance in a gritty, emotionally intense role.
-
E.
Sitarama
Sitarama is a revered epithet of the Hindu deity Rama that emphasizes his inseparable union with his consort Sita and their ideal of divine marital devotion.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156818cbc819086c956475ad23825 |
completed | April 16, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5a96e508190a64c2be6dc506e86 |
completed | May 9, 2026, 10:31 p.m. |
| NEDg | Description generation | batch_69ffb62f3d8881908ede4a9a4b53bef2 |
completed | May 9, 2026, 10:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffb6f3154481909632913f4d7cfdba |
completed | May 9, 2026, 10:36 p.m. |
Created at: April 10, 2026, 4:52 a.m.