Triple
T21600951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yashpal |
E533037
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Divya |
—
|
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: Divya | Statement: [Yashpal, notableWork, Divya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Divya Context triple: [Yashpal, notableWork, Divya]
-
A.
Divya
chosen
Divya is a renowned Kannada novel by U. R. Ananthamurthy that explores complex social and psychological themes in mid-20th-century India.
-
B.
Divya Saasha
Divya Saasha is the daughter of popular Indian actor Vijay, known for largely staying out of the public spotlight despite her father's fame.
-
C.
Aditi
Aditi is a Vedic mother goddess in Hindu mythology, revered as the personification of boundlessness and the mother of many deities.
-
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_69e0c46364608190a337dc8720dc2a35 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef17e12fdc8190ab6125ea8d294717 |
completed | April 27, 2026, 8:01 a.m. |
Created at: April 16, 2026, 6:32 p.m.