Triple
T20150541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tantravārttika |
E491422
|
entity |
| Predicate | relatedWork |
P37
|
FINISHED |
| Object | Ṭupṭīkā |
—
|
NE NERFINISHED |
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: Ṭupṭīkā | Statement: [Tantravārttika, relatedWork, Ṭupṭīkā]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ṭupṭīkā Context triple: [Tantravārttika, relatedWork, Ṭupṭīkā]
-
A.
Ṭupṭīkā
chosen
Ṭupṭīkā is a foundational Mīmāṃsā commentary traditionally attributed to the philosopher Kumārila Bhaṭṭa, elaborating and defending Vedic ritual exegesis.
-
B.
Sutrapada
Sutrapada is a coastal town in the Indian state of Gujarat, known for its proximity to the Arabian Sea and the Gir Somnath region.
-
C.
Tattvacintāmaṇi
Tattvacintāmaṇi is a foundational work of Indian logic and epistemology that systematizes the Navya-Nyāya school’s analysis of knowledge and inference.
-
D.
Sutikshna
Sutikshna is a sage in the Aranya Kanda of the Ramayana, known for offering hospitality and guidance to Rama, Sita, and Lakshmana during their exile in the forest.
-
E.
Upatiṣya
Upatiṣya is the personal name of Śāriputra, one of the Buddha’s foremost disciples renowned for his wisdom in early Buddhism.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667a1c5848190975b17ab07251f8b |
completed | April 20, 2026, 5:51 p.m. |
Created at: April 11, 2026, 11:33 p.m.