Triple
T20098880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Janaki |
E496478
|
entity |
| Predicate | cultCenter |
P9995
|
FINISHED |
| Object | Sitamarhi |
—
|
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: Sitamarhi | Statement: [Janaki, cultCenter, Sitamarhi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sitamarhi Context triple: [Janaki, cultCenter, Sitamarhi]
-
A.
Sitamarhi
chosen
Sitamarhi is a town in the Indian state of Bihar, historically associated with the legend of Sita’s birthplace and serving as an important local commercial and cultural center.
-
B.
Giridih
Giridih is a city in eastern India known for its coal and mica mining, situated in the Giridih district of the state of Jharkhand.
-
C.
Rampurhat
Rampurhat is a town and important railway junction in the Birbhum district of West Bengal, India.
-
D.
Medinipur
Medinipur is a parliamentary constituency and region in the Indian state of West Bengal, known for its historical significance and political importance.
-
E.
Muzaffarpur
Muzaffarpur is a major city in northern India known for its litchi production and role as an important commercial and educational center in the region.
- 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6666e306c81909c0ef617e0f6fccf |
completed | April 20, 2026, 5:46 p.m. |
Created at: April 11, 2026, 11:26 p.m.