Triple
T19969285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NH 16 |
E480026
|
entity |
| Predicate | connectsCity |
P4245
|
FINISHED |
| Object | Visakhapatnam |
—
|
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: Visakhapatnam | Statement: [NH 16, connectsCity, Visakhapatnam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Visakhapatnam Context triple: [NH 16, connectsCity, Visakhapatnam]
-
A.
Kakinada
Kakinada is a coastal city in the Indian state of Andhra Pradesh, known for its port, seafood industry, and role as a regional commercial hub.
-
B.
Vizagapatam
chosen
Vizagapatam, now commonly known as Visakhapatnam, is a major coastal city and port on the Bay of Bengal in present-day Andhra Pradesh, India.
-
C.
Nellore
Nellore is a prominent coastal city in southeastern India known for its agriculture, aquaculture, and role as an administrative and commercial center in Andhra Pradesh.
-
D.
Mehdipatnam
Mehdipatnam is a major residential and commercial neighborhood in Hyderabad, India, known for its busy markets, transport connectivity, and proximity to key city landmarks.
-
E.
Machilipatnam
Machilipatnam is a coastal city in the Indian state of Andhra Pradesh, historically known as a significant port and trading center on the Bay of Bengal.
- 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65bc7c2fc81909b89c549a5f99e4c |
completed | April 20, 2026, 5 p.m. |
Created at: April 10, 2026, 1:54 p.m.