Triple
T21412525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dollar Bahu |
E528208
|
entity |
| Predicate | televisionAdaptationTitle |
P83710
|
FINISHED |
| Object | Dollar Bahu |
—
|
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: Dollar Bahu | Statement: [Dollar Bahu, televisionAdaptationTitle, Dollar Bahu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dollar Bahu Context triple: [Dollar Bahu, televisionAdaptationTitle, Dollar Bahu]
-
A.
Dollar Bahu
chosen
Dollar Bahu is a popular Indian novel by Sudha Murty that explores family dynamics, materialism, and the cultural tensions between life in India and the United States.
-
B.
Dola
Dola is an island located within Lake Rakshastal in western Tibet, near the sacred Mount Kailash region.
-
C.
Bhadar
Bhadar is a river in the Saurashtra region of Gujarat, India, known for supporting irrigation and local ecosystems along its course.
-
D.
Ranchipur
Ranchipur is the fictional Indian princely city that serves as the central backdrop for Louis Bromfield’s novel and its film adaptation "The Rains Came."
-
E.
Bandiana
Bandiana is a suburb in the Australian state of Victoria, known primarily for its military facilities and proximity to the regional city of Wodonga.
- 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_69e0c454c248819093425d1099101c09 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee62d16bfc8190a1c08dd9d0c80e02 |
completed | April 26, 2026, 7:09 p.m. |
Created at: April 16, 2026, 5:44 p.m.