Triple

T36484469
Position Surface form Disambiguated ID Type / Status
Subject NRC IRAP E898899 entity
Predicate abbreviation P43 FINISHED
Object IRAP
IRAP is a Canadian federal program that supports small and medium-sized enterprises in developing and commercializing innovative technologies through advisory services and funding.
E2185129 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: IRAP | Statement: [NRC IRAP, abbreviation, IRAP]
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: IRAP
Triple: [NRC IRAP, abbreviation, IRAP]
Generated description
IRAP is a Canadian federal program that supports small and medium-sized enterprises in developing and commercializing innovative technologies through advisory services and funding.

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_69f76e5a0e088190a2b6706aeb41723c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7be01aa9481909504a163bb7a3423 completed May 3, 2026, 9:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39cfdefc7081908671067892fda4ae completed June 23, 2026, 12:14 a.m.
NEDg Description generation batch_6a39d06ec8448190bce52dd9dcb925f4 completed June 23, 2026, 12:16 a.m.
NED2 Entity disambiguation (via description) batch_6a39d12766ac8190a505dd6d49293937 completed June 23, 2026, 12:19 a.m.
Created at: May 3, 2026, 4:10 p.m.