Triple

T24102911
Position Surface form Disambiguated ID Type / Status
Subject Infinity Bridge E597135 entity
Predicate hasArchitect P184 FINISHED
Object Expedition Engineering
Expedition Engineering is a UK-based engineering consultancy known for its innovative structural and civil engineering work on landmark projects such as the Infinity Bridge.
E1615491 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: Expedition Engineering | Statement: [Infinity Bridge, hasArchitect, Expedition Engineering]
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: Expedition Engineering
Triple: [Infinity Bridge, hasArchitect, Expedition Engineering]
Generated description
Expedition Engineering is a UK-based engineering consultancy known for its innovative structural and civil engineering work on landmark projects such as the Infinity Bridge.

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_69e288c60f9c8190af948d7354aedbeb completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1dd2ad01881909aa5a3c300009086 completed April 29, 2026, 10:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f96829834819081c90817f65bf4d0 completed May 21, 2026, 11:34 p.m.
NEDg Description generation batch_6a0f96fc18f481909bac6d5e98f3966e completed May 21, 2026, 11:36 p.m.
NED2 Entity disambiguation (via description) batch_6a0f97e69c988190bfd0fb138248a226 completed May 21, 2026, 11:40 p.m.
Created at: April 17, 2026, 11 p.m.