Triple
T902458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramayana |
E19476
|
entity |
| Predicate | author |
P4
|
FINISHED |
| Object |
Valmiki
Valmiki is the revered ancient Indian sage traditionally credited with composing the epic Sanskrit poem Ramayana.
|
E108941
|
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: Valmiki | Statement: [Ramayana, author, Valmiki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Valmiki Context triple: [Ramayana, author, Valmiki]
-
A.
Vyasa
Vyasa is the legendary sage in Hindu tradition credited with composing and compiling the Mahabharata and organizing the Vedas.
-
B.
Nannaya
Nannaya is revered as the first great poet of Telugu literature, best known for initiating the classical Telugu rendition of the Mahabharata.
-
C.
Pāṇini
Pāṇini was an ancient Indian grammarian whose systematic and highly influential treatise, the Aṣṭādhyāyī, laid the foundations of classical Sanskrit grammar and linguistic analysis.
-
D.
Vatsyayana
Vatsyayana was an influential ancient Indian philosopher best known for his authoritative commentaries on the Nyaya school of logic and epistemology.
-
E.
Vidyapati
Vidyapati was a renowned medieval poet and scholar from the Mithila region, celebrated for his Maithili and Sanskrit devotional and love poetry.
- 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: Valmiki Triple: [Ramayana, author, Valmiki]
Generated description
Valmiki is the revered ancient Indian sage traditionally credited with composing the epic Sanskrit poem Ramayana.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Valmiki Target entity description: Valmiki is the revered ancient Indian sage traditionally credited with composing the epic Sanskrit poem Ramayana.
-
A.
Vyasa
Vyasa is the legendary sage in Hindu tradition credited with composing and compiling the Mahabharata and organizing the Vedas.
-
B.
Nannaya
Nannaya is revered as the first great poet of Telugu literature, best known for initiating the classical Telugu rendition of the Mahabharata.
-
C.
Pāṇini
Pāṇini was an ancient Indian grammarian whose systematic and highly influential treatise, the Aṣṭādhyāyī, laid the foundations of classical Sanskrit grammar and linguistic analysis.
-
D.
Vatsyayana
Vatsyayana was an influential ancient Indian philosopher best known for his authoritative commentaries on the Nyaya school of logic and epistemology.
-
E.
Vidyapati
Vidyapati was a renowned medieval poet and scholar from the Mithila region, celebrated for his Maithili and Sanskrit devotional and love poetry.
- 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_69a4939e889c8190ac148b3ac1a7f90b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad56f4c08190a7a5091ff0eb3209 |
completed | March 1, 2026, 9:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7cf5a4118819086035d6e250a53cc |
completed | March 4, 2026, 6:21 a.m. |
| NEDg | Description generation | batch_69a7d082b4388190bcf04692c273e5cc |
completed | March 4, 2026, 6:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7d49784d08190b334de4fe634f1c6 |
completed | March 4, 2026, 6:43 a.m. |
Created at: March 1, 2026, 7:39 p.m.