Triple

T29466075
Position Surface form Disambiguated ID Type / Status
Subject Buyid family E747382 entity
Predicate hasMember P10 FINISHED
Object Abu Kalijar
Abu Kalijar was a prominent 11th-century Buyid ruler who controlled large parts of Iraq and Iran during the dynasty’s later period.
E1881136 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: Abu Kalijar | Statement: [Buyid family, hasMember, Abu Kalijar]
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: Abu Kalijar
Triple: [Buyid family, hasMember, Abu Kalijar]
Generated description
Abu Kalijar was a prominent 11th-century Buyid ruler who controlled large parts of Iraq and Iran during the dynasty’s later period.

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_69f0bd4125f88190b56104591351619c completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66ba7afcc8190a98cfe4f88ab7bc7 completed May 2, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26aa5818b8819085ade43bb1512f01 completed June 8, 2026, 11:41 a.m.
NEDg Description generation batch_6a26b01a27148190aa0135f779819255 completed June 8, 2026, 12:05 p.m.
NED2 Entity disambiguation (via description) batch_6a26b4f2ca348190b487f39e75b45b4f completed June 8, 2026, 12:26 p.m.
Created at: April 28, 2026, 3:53 p.m.