Triple
T20146265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nagpur oranges |
E491309
|
entity |
| Predicate | marketedAs |
P1395
|
FINISHED |
| Object | Nagpur mandarin |
—
|
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: Nagpur mandarin | Statement: [Nagpur oranges, marketedAs, Nagpur mandarin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nagpur mandarin Context triple: [Nagpur oranges, marketedAs, Nagpur mandarin]
-
A.
Nagpur oranges
chosen
Nagpur oranges are a distinctive, sweet-tangy citrus variety from the Nagpur region of Maharashtra, India, renowned across the country for their flavor and quality.
-
B.
Litchi City of India
Litchi City of India is the popular nickname for Muzaffarpur, a city in Bihar renowned for its high-quality litchi production.
-
C.
Nagpur
Nagpur is a major city in the Indian state of Maharashtra, known as a key political and commercial center and often referred to as the "Orange City" for its famous orange production.
-
D.
Malvani
Malvani is an Indo-Aryan language variety spoken primarily in the Konkan coastal region of Maharashtra and Goa, closely related to Marathi and Konkani.
-
E.
Mehsana
Mehsana is a prominent city in the Indian state of Gujarat, known for its dairy industry, oil and natural gas fields, and historical temples.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6679e43a48190b3a5da5710b07ff7 |
completed | April 20, 2026, 5:51 p.m. |
Created at: April 11, 2026, 11:33 p.m.