Triple

T29995482
Position Surface form Disambiguated ID Type / Status
Subject Eilandje district E762009 entity
Predicate hasLandmark P105 FINISHED
Object London Bridge (Antwerp)
London Bridge (Antwerp) is a historic steel swing bridge in Antwerp’s Eilandje district, notable for its industrial heritage and role in connecting the old port area.
E1894841 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: London Bridge (Antwerp) | Statement: [Eilandje district, hasLandmark, London Bridge (Antwerp)]
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: London Bridge (Antwerp)
Triple: [Eilandje district, hasLandmark, London Bridge (Antwerp)]
Generated description
London Bridge (Antwerp) is a historic steel swing bridge in Antwerp’s Eilandje district, notable for its industrial heritage and role in connecting the old port area.

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_69f224695498819094a81037cad401e2 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f6791e4bdc8190b65309a7271ee68f completed May 2, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27220552608190b59037ed2f7bbee0 completed June 8, 2026, 8:11 p.m.
NEDg Description generation batch_6a2725075a288190abbea73a8307ae79 completed June 8, 2026, 8:24 p.m.
NED2 Entity disambiguation (via description) batch_6a2725ec27e88190b1433f05533290bd completed June 8, 2026, 8:28 p.m.
Created at: April 29, 2026, 6:39 p.m.