Triple
T28712187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jagjit Singh |
E729858
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Tumko Dekha To Yeh Khayal Aaya
"Tumko Dekha To Yeh Khayal Aaya" is a popular Hindi ghazal, widely cherished for its soulful melody and romantic, introspective lyrics, sung by legendary ghazal singer Jagjit Singh.
|
E1830205
|
NE FINISHED |
How this triple was built (2 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: Tumko Dekha To Yeh Khayal Aaya | Statement: [Jagjit Singh, notableWork, Tumko Dekha To Yeh Khayal Aaya]
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: Tumko Dekha To Yeh Khayal Aaya Triple: [Jagjit Singh, notableWork, Tumko Dekha To Yeh Khayal Aaya]
Generated description
"Tumko Dekha To Yeh Khayal Aaya" is a popular Hindi ghazal, widely cherished for its soulful melody and romantic, introspective lyrics, sung by legendary ghazal singer Jagjit Singh.
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_69f043e7d5a4819094b18aca10b1e024 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f656d92c088190918720a02e2d923c |
completed | May 2, 2026, 7:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1ccf542a848190a044c22a54e9c5ee |
completed | June 1, 2026, 12:16 a.m. |
| NEDg | Description generation | batch_6a1ccff9242081908a415b1d68855a63 |
completed | June 1, 2026, 12:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a249457116881909199d0b381a902c3 |
completed | June 6, 2026, 9:42 p.m. |
Created at: April 28, 2026, 5:48 a.m.