Triple

T29739189
Position Surface form Disambiguated ID Type / Status
Subject MQPUT E752547 entity
Predicate documentedIn P309 FINISHED
Object IBM MQ Application Programming Reference
IBM MQ Application Programming Reference is an IBM manual that provides detailed technical guidance and API documentation for developing applications that use IBM MQ messaging.
E41050 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: IBM MQ Application Programming Reference | Statement: [MQPUT, documentedIn, IBM MQ Application Programming Reference]
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: IBM MQ Application Programming Reference
Triple: [MQPUT, documentedIn, IBM MQ Application Programming Reference]
Generated description
IBM MQ Application Programming Reference is an IBM manual that provides detailed technical guidance and API documentation for developing applications that use IBM MQ messaging.

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_69f0d62b064081908c1ae61cd68fb139 completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f67336d44881908c3580e1ebb15bcf completed May 2, 2026, 9:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26aa8c328881909885f6674c8c7a24 completed June 8, 2026, 11:42 a.m.
NEDg Description generation batch_6a26b58435608190bd536ba9566012a1 completed June 8, 2026, 12:28 p.m.
NED2 Entity disambiguation (via description) batch_6a26b71d306081908a97e1af6266bf6a completed June 8, 2026, 12:35 p.m.
Created at: April 28, 2026, 7:47 p.m.