Triple

T27452670
Position Surface form Disambiguated ID Type / Status
Subject Stalowa Wola E692490 entity
Predicate partOf P40 FINISHED
Object Central Industrial Region
The Central Industrial Region was a major pre-World War II Polish economic development project focused on building heavy industry and strengthening the country’s defense capabilities in its central and southeastern areas.
E1771849 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: Central Industrial Region | Statement: [Stalowa Wola, partOf, Central Industrial Region]
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: Central Industrial Region
Triple: [Stalowa Wola, partOf, Central Industrial Region]
Generated description
The Central Industrial Region was a major pre-World War II Polish economic development project focused on building heavy industry and strengthening the country’s defense capabilities in its central and southeastern areas.

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_69ef5206c9248190b5975c2a7f9d229c completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62dc69f1481908717ae77e60d9658 completed May 2, 2026, 5 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12b260e6f481909076075270653c1c completed May 24, 2026, 8:10 a.m.
NEDg Description generation batch_6a12b32353248190ac509d73a9910602 completed May 24, 2026, 8:13 a.m.
NED2 Entity disambiguation (via description) batch_6a12b3c695a0819099113dba54710362 completed May 24, 2026, 8:16 a.m.
Created at: April 27, 2026, 12:48 p.m.