Triple

T26242670
Position Surface form Disambiguated ID Type / Status
Subject FloEFD E656355 entity
Predicate developedBy P73 FINISHED
Object Siemens Digital Industries Software
Siemens Digital Industries Software is a global provider of engineering and manufacturing software solutions that support product design, simulation, and lifecycle management across various industries.
E1718450 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: Siemens Digital Industries Software | Statement: [FloEFD, developedBy, Siemens Digital Industries Software]
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: Siemens Digital Industries Software
Triple: [FloEFD, developedBy, Siemens Digital Industries Software]
Generated description
Siemens Digital Industries Software is a global provider of engineering and manufacturing software solutions that support product design, simulation, and lifecycle management across various industries.

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_69ee5b4c59a881909d9ee4fd013fffd5 completed April 26, 2026, 6:37 p.m.
NER Named-entity recognition batch_69f60d90a5908190a7ccff2bd50ffe73 completed May 2, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a118faa68a48190aa7023ef73694612 completed May 23, 2026, 11:29 a.m.
NEDg Description generation batch_6a119138c294819085da49e898c33028 completed May 23, 2026, 11:36 a.m.
NED2 Entity disambiguation (via description) batch_6a11919f20d0819085f4ca53f9883f38 completed May 23, 2026, 11:38 a.m.
Created at: April 26, 2026, 9:04 p.m.