Triple
T1410187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kartikeya |
E31785
|
entity |
| Predicate | otherName |
P39
|
FINISHED |
| Object | Shanmuga |
E111277
|
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: Shanmuga | Statement: [Kartikeya, otherName, Shanmuga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shanmuga Context triple: [Kartikeya, otherName, Shanmuga]
-
A.
Murugan
chosen
Murugan is a prominent Hindu deity of war and victory, especially revered in South India and Sri Lanka, often depicted as a youthful god with a spear and associated with wisdom and valor.
-
B.
Shabara Svamin
Shabara Svamin was an influential early Indian philosopher and commentator whose work on the Mimamsa school’s foundational texts significantly shaped Hindu ritual and hermeneutic thought.
-
C.
Guna
Guna is a city in the central Indian state of Madhya Pradesh known as an important regional administrative and commercial center.
-
D.
Kesava
Kesava is a revered epithet of the Hindu god Vishnu, highlighting him as the slayer of the demon Keshi and the one with beautiful, luxuriant hair.
-
E.
Venkata
Venkata is the given name of Indian physicist and Nobel laureate C. V. Raman, renowned for discovering the Raman effect in light scattering.
- 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_69a49918e1f88190ba610f9dc8114578 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3e0bfd08190a50820bc7585c28f |
completed | March 1, 2026, 10:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad0e67dbf88190a2a15baca5b9e79d |
completed | March 8, 2026, 5:51 a.m. |
Created at: March 1, 2026, 7:59 p.m.