Triple
T31785133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surma River basin |
E811306
|
entity |
| Predicate | hasMajorRiver |
P165
|
FINISHED |
| Object |
Jadukata River
Jadukata River is a significant transboundary river in the Surma basin of northeastern India and Bangladesh, known for its scenic course through the Meghalaya hills and its role in regional agriculture and fisheries.
|
E2295975
|
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: Jadukata River | Statement: [Surma River basin, hasMajorRiver, Jadukata River]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Jadukata River Triple: [Surma River basin, hasMajorRiver, Jadukata River]
Generated description
Jadukata River is a significant transboundary river in the Surma basin of northeastern India and Bangladesh, known for its scenic course through the Meghalaya hills and its role in regional agriculture and fisheries.
Provenance (5 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_69f348e544a48190ab6e700b05f6438c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6abe872f88190beb7aff9ace13bbf |
completed | May 3, 2026, 1:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a821974f3048190b46e3480b9fdec6c |
completed | Aug. 16, 2026, 8:11 p.m. |
| NEDg | Description generation | batch_6a821bd940dc8190bd168dcc5fa4f953 |
completed | Aug. 16, 2026, 8:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a821c2cfab4819085721ed36d327032 |
completed | Aug. 16, 2026, 8:23 p.m. |
Created at: April 30, 2026, 11:37 p.m.