Triple
T21620375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Satyam |
E533558
|
entity |
| Predicate | relatedConcept |
P37
|
FINISHED |
| Object | Satya |
—
|
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: Satya | Statement: [Satyam, relatedConcept, Satya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Satya Context triple: [Satyam, relatedConcept, Satya]
-
A.
Satya
Satya is the given name of Satya Nandan, a prominent Fijian diplomat and former United Nations official known for his work in international maritime law.
-
B.
Satya
chosen
Satya is the ancient Indian philosophical concept of truth, encompassing moral integrity, honesty, and alignment with cosmic order.
-
C.
Satyakam
Satyakam is a critically acclaimed 1969 Hindi drama film directed by Hrishikesh Mukherjee, known for its exploration of idealism, morality, and social change in post-independence India.
-
D.
Kaalpurush
Kaalpurush is an acclaimed Bengali film by director Buddhadeb Dasgupta that explores memory, time, and human relationships through a poetic, surreal narrative.
-
E.
Nayakan
Nayakan is a critically acclaimed 1987 Tamil crime drama film directed by Mani Ratnam, renowned for Kamal Haasan’s powerful performance and its portrayal of a Mumbai underworld don.
- 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_69e0c464fba881908d0ff2ac80511ce1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef3baeeae48190b78583b3bec8ee33 |
completed | April 27, 2026, 10:34 a.m. |
Created at: April 16, 2026, 6:34 p.m.