Triple
T1083361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pāṇini |
E23996
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object | Kātyāyana |
E111940
|
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: Kātyāyana | Statement: [Pāṇini, influenced, Kātyāyana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kātyāyana Context triple: [Pāṇini, influenced, Kātyāyana]
-
A.
Vatsyayana
Vatsyayana was an influential ancient Indian philosopher best known for his authoritative commentaries on the Nyaya school of logic and epistemology.
-
B.
Aṣṭādhyāyī
Aṣṭādhyāyī is an ancient and highly systematic Sanskrit grammar treatise that forms the foundational work of the grammatical tradition attributed to the scholar Pāṇini.
-
C.
Samhita
Samhita is the mantra-collection portion of the Yajurveda, comprising its core liturgical hymns and formulas used in Vedic rituals.
-
D.
Katyayana Smriti
chosen
Katyayana Smriti is an ancient Hindu legal and ethical text attributed to the sage Katyayana, forming part of the classical Dharmashastra tradition.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b95e56948190a1e92367ad7240b7 |
completed | March 1, 2026, 10:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4c243cbc81908d6101faad628fc8 |
completed | March 7, 2026, 4:02 p.m. |
Created at: March 1, 2026, 7:42 p.m.