Triple

T37839986
Position Surface form Disambiguated ID Type / Status
Subject Port of Raahe E943446 entity
Predicate operator P179 FINISHED
Object Port of Raahe Ltd
Port of Raahe Ltd is the company responsible for managing and operating the Port of Raahe, a key Finnish seaport serving industrial and cargo traffic on the northern Baltic Sea.
E2244878 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: Port of Raahe Ltd | Statement: [Port of Raahe, operator, Port of Raahe Ltd]
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: Port of Raahe Ltd
Triple: [Port of Raahe, operator, Port of Raahe Ltd]
Generated description
Port of Raahe Ltd is the company responsible for managing and operating the Port of Raahe, a key Finnish seaport serving industrial and cargo traffic on the northern Baltic Sea.

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_69f76eeb0f7081908d6d3adbc469889c completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbb21a7d988190bbd9e3b83961c6e6 completed May 6, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40fb8a7f1081908705b7d1507bb05e completed June 28, 2026, 10:46 a.m.
NEDg Description generation batch_6a40fc247b7081908d545d61ba115664 completed June 28, 2026, 10:49 a.m.
NED2 Entity disambiguation (via description) batch_6a40fca727148190bf102c874b747b38 completed June 28, 2026, 10:51 a.m.
Created at: May 3, 2026, 4:19 p.m.