Triple
T21381404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iravati River |
E527364
|
entity |
| Predicate | ancientName |
P2834
|
FINISHED |
| Object | Parushni |
—
|
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: Parushni | Statement: [Iravati River, ancientName, Parushni]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Parushni Context triple: [Iravati River, ancientName, Parushni]
-
A.
Parushni
chosen
Parushni is the ancient Vedic name for the Ravi River, one of the major rivers of the northwestern Indian subcontinent.
-
B.
Shivini
Shivini is the Urartian sun god, often associated with light, justice, and royal authority in the ancient Kingdom of Urartu.
-
C.
Sharmishta
Sharmishta is the full given name of Shami Chakrabarti, a prominent British barrister and human rights advocate.
-
D.
Urvashi
Urvashi is a celebrated apsara (celestial nymph) in Hindu mythology, renowned for her beauty and her tragic love story with the mortal king Pururavas.
-
E.
Urvashi
Urvashi is a prominent Indian film actress best known for her versatile performances in Malayalam cinema, along with notable roles in Tamil, Telugu, and Kannada films.
- 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_69e0b51f363c8190944000ab5523b02b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b0cec99881908481d0b08df358a8 |
completed | April 22, 2026, 11:28 a.m. |
Created at: April 16, 2026, 5:11 p.m.