Triple
T28841799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kolkata Metropolitan Development Authority |
E728336
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
KMDA
KMDA is the statutory planning and development authority responsible for infrastructure and urban development in the Kolkata metropolitan region of India.
|
E1836375
|
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: KMDA | Statement: [Kolkata Metropolitan Development Authority, shortName, KMDA]
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: KMDA Triple: [Kolkata Metropolitan Development Authority, shortName, KMDA]
Generated description
KMDA is the statutory planning and development authority responsible for infrastructure and urban development in the Kolkata metropolitan region of India.
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_69f0319e8e7c8190b37288c8845b9dbc |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f6597388608190b0bcb812f4484f62 |
completed | May 2, 2026, 8:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a24bbb54c6c819088c0a7d269fdcc60 |
completed | June 7, 2026, 12:30 a.m. |
| NEDg | Description generation | batch_6a24c12a5b548190aa6228a4fe0d200f |
completed | June 7, 2026, 12:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a24c55ba59c81908fcfff015a36e2c0 |
completed | June 7, 2026, 1:11 a.m. |
Created at: April 28, 2026, 6:41 a.m.