Triple

T29995506
Position Surface form Disambiguated ID Type / Status
Subject Bonapartedok E762010 entity
Predicate locatedIn P40 FINISHED
Object Antwerp old port area
The Antwerp old port area is a historic docklands district of Antwerp, Belgium, characterized by its former commercial harbors, warehouses, and redeveloped waterfront spaces.
 E1897890 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: Antwerp old port area | Statement: [Bonapartedok, locatedIn, Antwerp old port area]
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: Antwerp old port area
Triple: [Bonapartedok, locatedIn, Antwerp old port area]
Generated description
The Antwerp old port area is a historic docklands district of Antwerp, Belgium, characterized by its former commercial harbors, warehouses, and redeveloped waterfront spaces.

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_6a273224db3081909829e1bfb09b8c16 completed June 8, 2026, 9:20 p.m.
NEDg Description generation batch_6a273412bb148190b807e5f7054478e3 completed June 8, 2026, 9:28 p.m.
NED2 Entity disambiguation (via description) batch_6a2734afdee081908b9e8400be7766da completed June 8, 2026, 9:31 p.m.
Created at: April 29, 2026, 6:39 p.m.