Triple

T26259844
Position Surface form Disambiguated ID Type / Status
Subject Chinsurah E656816 entity
Predicate hasHeritageStructure P1098 FINISHED
Object Dutch cemetery, Chinsurah
The Dutch cemetery in Chinsurah is a historic burial ground dating back to the Dutch colonial period in Bengal, notable for its old tombs and monuments reflecting European funerary architecture.
E1715090 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: Dutch cemetery, Chinsurah | Statement: [Chinsurah, hasHeritageStructure, Dutch cemetery, Chinsurah]
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: Dutch cemetery, Chinsurah
Triple: [Chinsurah, hasHeritageStructure, Dutch cemetery, Chinsurah]
Generated description
The Dutch cemetery in Chinsurah is a historic burial ground dating back to the Dutch colonial period in Bengal, notable for its old tombs and monuments reflecting European funerary architecture.

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_69ee5b4e21bc819082be98bc9ab09796 completed April 26, 2026, 6:37 p.m.
NER Named-entity recognition batch_69f60dfdd57c81908d069fc4b8124ff7 completed May 2, 2026, 2:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1185ad7bc08190ad17fe8180a1fe58 completed May 23, 2026, 10:47 a.m.
NEDg Description generation batch_6a11865b89b88190bb7786de150068e9 completed May 23, 2026, 10:50 a.m.
NED2 Entity disambiguation (via description) batch_6a1186d8c7bc81909c851862b3a29e13 completed May 23, 2026, 10:52 a.m.
Created at: April 26, 2026, 9:09 p.m.