Triple

T29881870
Position Surface form Disambiguated ID Type / Status
Subject Chief Minister of Kerala E758898 entity
Predicate residence P75 FINISHED
Object Cliff House, Thiruvananthapuram
Cliff House, Thiruvananthapuram is the official government bungalow that serves as the residence of the sitting Chief Minister of Kerala.
E1889235 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: Cliff House, Thiruvananthapuram | Statement: [Chief Minister of Kerala, residence, Cliff House, Thiruvananthapuram]
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: Cliff House, Thiruvananthapuram
Triple: [Chief Minister of Kerala, residence, Cliff House, Thiruvananthapuram]
Generated description
Cliff House, Thiruvananthapuram is the official government bungalow that serves as the residence of the sitting Chief Minister of Kerala.

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_69f2245de2f48190a481404896b56254 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f676fa71dc819081a2344883843e7b completed May 2, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26f1d9f6948190aabc4473db299911 completed June 8, 2026, 4:46 p.m.
NEDg Description generation batch_6a26f2c9c08481908041d7b5f11d9ab6 completed June 8, 2026, 4:50 p.m.
NED2 Entity disambiguation (via description) batch_6a26f4479b0c8190951c45e5d0c6f098 completed June 8, 2026, 4:56 p.m.
Created at: April 29, 2026, 5:58 p.m.