Triple
T22591183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hindu pantheon |
E564951
|
entity |
| Predicate | hasDeity |
P5606
|
FINISHED |
| Object | Matsya |
—
|
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: Matsya | Statement: [Hindu pantheon, hasDeity, Matsya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matsya Context triple: [Hindu pantheon, hasDeity, Matsya]
-
A.
Matsya
Matsya was an ancient Indo-Aryan kingdom of northwestern India, often associated with the region around modern Rajasthan and mentioned in early Vedic and epic literature.
-
B.
Matsya
chosen
Matsya is the fish incarnation of the Hindu god Vishnu, known for saving the sacred scriptures and the first man from a great deluge.
-
C.
Matsya avatar
The Matsya avatar is the fish incarnation of the Hindu god Vishnu, known for saving the first man and the sacred scriptures from a great deluge.
-
D.
Garsaura
Garsaura was an ancient settlement in central Anatolia, known as the historical predecessor of the modern Turkish city of Aksaray.
-
E.
Ikan
Ikan is an alternative name for the Ukaan language, a lesser-known Niger-Congo language spoken in parts of Nigeria.
- 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_69e245836014819091b91ed3074742a3 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f16160651081909d23735336fd7a16 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 2:48 p.m.