Triple

T23920433
Position Surface form Disambiguated ID Type / Status
Subject Institution of Structural Engineers E602198 entity
Predicate postNominal P1610 FINISHED
Object MIStructE
MIStructE is a professional post-nominal title indicating a Member of the Institution of Structural Engineers, recognizing qualified structural engineering professionals.
E1611129 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: MIStructE | Statement: [Institution of Structural Engineers, postNominal, MIStructE]
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: MIStructE
Triple: [Institution of Structural Engineers, postNominal, MIStructE]
Generated description
MIStructE is a professional post-nominal title indicating a Member of the Institution of Structural Engineers, recognizing qualified structural engineering professionals.

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_69e2953a187081908346a9f36e85fc98 completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f1cf1772e08190a434c91f4e7437b4 completed April 29, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f763db7f48190b8904ae466c9de52 completed May 21, 2026, 9:16 p.m.
NEDg Description generation batch_6a0f77490b248190a3eee26e9fd81d0a completed May 21, 2026, 9:21 p.m.
NED2 Entity disambiguation (via description) batch_6a0f77bd3f688190bbc8612330e6a5f0 completed May 21, 2026, 9:23 p.m.
Created at: April 17, 2026, 8:41 p.m.