Triple
T1410184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kartikeya |
E31785
|
entity |
| Predicate | otherName |
P39
|
FINISHED |
| Object |
Subramanya
Subramanya is a Hindu deity of war and wisdom, widely revered in South India and identified with the god Kartikeya (Murugan).
|
E164754
|
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: Subramanya | Statement: [Kartikeya, otherName, Subramanya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Subramanya Context triple: [Kartikeya, otherName, Subramanya]
-
A.
Naraina
Naraina is a locality in West Delhi, India, known for its mix of residential areas and industrial estates and its location along major city transport routes.
-
B.
Narayana
Narayana is a revered name of the Hindu god Vishnu, especially associated with his role as the supreme preserver and sustainer of the universe.
-
C.
Venkata
Venkata is the given name of Indian physicist and Nobel laureate C. V. Raman, renowned for discovering the Raman effect in light scattering.
-
D.
Bhavani
Bhavani is a significant river in southern India, known for flowing through Tamil Nadu and contributing majorly to the Kaveri river system.
-
E.
Bhavani
Bhavani is a fierce and protective form of the Hindu goddess Devi, often associated with power, motherhood, and the destruction of evil.
- 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: Subramanya Triple: [Kartikeya, otherName, Subramanya]
Generated description
Subramanya is a Hindu deity of war and wisdom, widely revered in South India and identified with the god Kartikeya (Murugan).
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Subramanya Target entity description: Subramanya is a Hindu deity of war and wisdom, widely revered in South India and identified with the god Kartikeya (Murugan).
-
A.
Naraina
Naraina is a locality in West Delhi, India, known for its mix of residential areas and industrial estates and its location along major city transport routes.
-
B.
Narayana
Narayana is a revered name of the Hindu god Vishnu, especially associated with his role as the supreme preserver and sustainer of the universe.
-
C.
Venkata
Venkata is the given name of Indian physicist and Nobel laureate C. V. Raman, renowned for discovering the Raman effect in light scattering.
-
D.
Bhavani
Bhavani is a significant river in southern India, known for flowing through Tamil Nadu and contributing majorly to the Kaveri river system.
-
E.
Bhavani
Bhavani is a fierce and protective form of the Hindu goddess Devi, often associated with power, motherhood, and the destruction of evil.
- 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_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_69ad08ae530081909695bde0d9c46d41 |
completed | March 8, 2026, 5:27 a.m. |
| NEDg | Description generation | batch_69ad0975b0c4819095a36f833e15fdae |
completed | March 8, 2026, 5:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad0a1df32c81908bf57911901f3f9c |
completed | March 8, 2026, 5:33 a.m. |
Created at: March 1, 2026, 7:59 p.m.