Triple

T25678599
Position Surface form Disambiguated ID Type / Status
Subject Park Street area E643874 entity
Predicate hasRoad P959 FINISHED
Object Mother Teresa Sarani
Mother Teresa Sarani is a major thoroughfare in central Kolkata, India, historically known as Park Street and famous for its restaurants, nightlife, and colonial-era landmarks.
 E1691078 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: Mother Teresa Sarani | Statement: [Park Street area, hasRoad, Mother Teresa Sarani]
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: Mother Teresa Sarani
Triple: [Park Street area, hasRoad, Mother Teresa Sarani]
Generated description
Mother Teresa Sarani is a major thoroughfare in central Kolkata, India, historically known as Park Street and famous for its restaurants, nightlife, and colonial-era landmarks.

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_69e77e7f69808190ad27df1006f6037a completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5fb77c3a08190b63e811dd21989fd completed May 2, 2026, 1:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10c15f52fc8190a4b36a72c9f7b89f completed May 22, 2026, 8:49 p.m.
NEDg Description generation batch_6a10c22b19a48190b04130bdb7763f0a completed May 22, 2026, 8:52 p.m.
NED2 Entity disambiguation (via description) batch_6a10c2de07648190858ba8901748aa53 completed May 22, 2026, 8:55 p.m.
Created at: April 21, 2026, 7:43 p.m.