Triple

T36186088
Position Surface form Disambiguated ID Type / Status
Subject Azam Jah E1046848 entity
Predicate fullName P16 FINISHED
Object Mir Himayat Ali Khan Azam Jah
Mir Himayat Ali Khan Azam Jah was the eldest son and heir apparent of the last Nizam of Hyderabad, Osman Ali Khan, and a prominent prince of the former Hyderabad State in India.
E2193243 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: Mir Himayat Ali Khan Azam Jah | Statement: [Azam Jah, fullName, Mir Himayat Ali Khan Azam Jah]
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: Mir Himayat Ali Khan Azam Jah
Triple: [Azam Jah, fullName, Mir Himayat Ali Khan Azam Jah]
Generated description
Mir Himayat Ali Khan Azam Jah was the eldest son and heir apparent of the last Nizam of Hyderabad, Osman Ali Khan, and a prominent prince of the former Hyderabad State in 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_69f76e3d4fbc81908c159c7beeb4ce00 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b51473888190a5668f3a0ae248c4 completed May 3, 2026, 8:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3a20ad06e8819097dd458e548f8b7f completed June 23, 2026, 5:59 a.m.
NEDg Description generation batch_6a3a21d045cc81908d61119fb621f7b6 completed June 23, 2026, 6:04 a.m.
NED2 Entity disambiguation (via description) batch_6a3a225b99788190bafbd7ccb4a652b9 completed June 23, 2026, 6:06 a.m.
Created at: May 3, 2026, 4:08 p.m.