Triple
T21240343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Narayan Guru |
E523452
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Arivu
Arivu is a notable philosophical and spiritual work by the revered Indian social reformer and saint Narayana Guru.
|
E1473206
|
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: Arivu | Statement: [Narayan Guru, notableWork, Arivu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arivu Context triple: [Narayan Guru, notableWork, Arivu]
-
A.
Elavarkuzhali
Elavarkuzhali is a revered form of the Hindu goddess Parvati worshipped at the Ekambareswarar Temple in Kanchipuram.
-
B.
Uthangarai
Uthangarai is a town in the southern Indian state of Tamil Nadu, known as a local commercial and educational center for the surrounding rural region.
-
C.
Velaikkaran
Velaikkaran is a 2017 Tamil-language social drama film starring Sivakarthikeyan that focuses on corporate corruption and the struggles of exploited workers.
-
D.
Aravaan
Aravaan is a variant name of Aravan, a character from the Indian epic Mahabharata who is venerated in certain regional and religious traditions.
-
E.
Vedalam
Vedalam is a 2015 Tamil-language action film starring Ajith Kumar, known for its mass appeal, high-octane fight sequences, and emotional brother-sister storyline.
- 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: Arivu Triple: [Narayan Guru, notableWork, Arivu]
Generated description
Arivu is a notable philosophical and spiritual work by the revered Indian social reformer and saint Narayana Guru.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Arivu Target entity description: Arivu is a notable philosophical and spiritual work by the revered Indian social reformer and saint Narayana Guru.
-
A.
Elavarkuzhali
Elavarkuzhali is a revered form of the Hindu goddess Parvati worshipped at the Ekambareswarar Temple in Kanchipuram.
-
B.
Uthangarai
Uthangarai is a town in the southern Indian state of Tamil Nadu, known as a local commercial and educational center for the surrounding rural region.
-
C.
Velaikkaran
Velaikkaran is a 2017 Tamil-language social drama film starring Sivakarthikeyan that focuses on corporate corruption and the struggles of exploited workers.
-
D.
Aravaan
Aravaan is a variant name of Aravan, a character from the Indian epic Mahabharata who is venerated in certain regional and religious traditions.
-
E.
Vedalam
Vedalam is a 2015 Tamil-language action film starring Ajith Kumar, known for its mass appeal, high-octane fight sequences, and emotional brother-sister storyline.
- 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_69e0b513b89c81908b27147e91368db2 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e73522acdc8190b3e155026a0445cd |
completed | April 21, 2026, 8:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0986f235b08190bd0a7ded7e1c9cbc |
completed | May 17, 2026, 9:14 a.m. |
| NEDg | Description generation | batch_6a09877c03508190ae15fc181e3cc05e |
completed | May 17, 2026, 9:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09884d294c8190911935ae7b162b1f |
completed | May 17, 2026, 9:20 a.m. |
Created at: April 16, 2026, 3:46 p.m.