Triple
T26978783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krishnam Raju |
E679533
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Manavoori Pandavulu
Manavoori Pandavulu is a 1978 Telugu-language action drama film celebrated for its ensemble cast, social-reform theme, and status as a landmark in Telugu cinema.
|
E1756326
|
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: Manavoori Pandavulu | Statement: [Krishnam Raju, notableWork, Manavoori Pandavulu]
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: Manavoori Pandavulu Triple: [Krishnam Raju, notableWork, Manavoori Pandavulu]
Generated description
Manavoori Pandavulu is a 1978 Telugu-language action drama film celebrated for its ensemble cast, social-reform theme, and status as a landmark in Telugu cinema.
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_69eeeb507a7081909d516e1fa08b7d29 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f621548d9081908cd4540b909d01f6 |
completed | May 2, 2026, 4:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1247ea50f081909b316177aec0a557 |
completed | May 24, 2026, 12:35 a.m. |
| NEDg | Description generation | batch_6a1248ceac908190a0264122d588ecba |
completed | May 24, 2026, 12:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a1249c660a48190888d98cfc14506b0 |
completed | May 24, 2026, 12:43 a.m. |
Created at: April 27, 2026, 6:44 a.m.