Triple
T13176629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ratnagiri railway station |
E313113
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Ratnagiri city |
E79536
|
NE FINISHED |
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: Ratnagiri city | Statement: [Ratnagiri railway station, locatedIn, Ratnagiri city]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ratnagiri city Context triple: [Ratnagiri railway station, locatedIn, Ratnagiri city]
-
A.
Ratnagiri
chosen
Ratnagiri is a coastal city in Maharashtra, India, known for its Alphonso mangoes, historic forts, and scenic beaches along the Konkan coast.
-
B.
Baramati
Baramati is a town in the Pune district of Maharashtra, India, known as an agricultural and industrial hub with historical and political significance.
-
C.
Malegaon
Malegaon is a major textile and powerloom town in Maharashtra, India, known for its large Muslim population and vibrant weaving industry.
-
D.
Kolhapur
Kolhapur is a historic city in the Indian state of Maharashtra, known for its rich Maratha heritage, temples, and distinctive Kolhapuri cuisine and leather sandals.
-
E.
Madgaon
Madgaon is a major commercial and cultural city in the South Goa district of the Indian state of Goa.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d806ac3ee081909b2fd27d060aa974 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c322fdc8190b05f2287eba9dda6 |
completed | April 10, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f72660f8d48190b437a57f2a75f6ae |
completed | May 3, 2026, 10:41 a.m. |
Created at: April 9, 2026, 9:14 p.m.