Triple

T29312898
Position Surface form Disambiguated ID Type / Status
Subject Old-Polish Industrial Region E743292 entity
Predicate hasPolishName P15778 FINISHED
Object Staropolski Okręg Przemysłowy
Staropolski Okręg Przemysłowy is a historic industrial region in central Poland, traditionally centered around metallurgy, mining, and manufacturing.
E1861792 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: Staropolski Okręg Przemysłowy | Statement: [Old-Polish Industrial Region, hasPolishName, Staropolski Okręg Przemysłowy]
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: Staropolski Okręg Przemysłowy
Triple: [Old-Polish Industrial Region, hasPolishName, Staropolski Okręg Przemysłowy]
Generated description
Staropolski Okręg Przemysłowy is a historic industrial region in central Poland, traditionally centered around metallurgy, mining, and manufacturing.

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_69f0912502c8819087d9e8398ee991a8 completed April 28, 2026, 10:51 a.m.
NER Named-entity recognition batch_69f665e75bf48190ae1887c28a6003b9 completed May 2, 2026, 9 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25a86c38fc819086372adeade1e263 completed June 7, 2026, 5:20 p.m.
NEDg Description generation batch_6a25accca754819087850f98ba074aeb completed June 7, 2026, 5:39 p.m.
NED2 Entity disambiguation (via description) batch_6a25b146e9d0819086b956ae8ea30aab completed June 7, 2026, 5:58 p.m.
Created at: April 28, 2026, 1:18 p.m.