Triple

T31044660
Position Surface form Disambiguated ID Type / Status
Subject Przemyśl Fortress E791089 entity
Predicate hasPart P35 FINISHED
Object Fort XXXV Borek
Fort XXXV Borek is one of the defensive works of the Austro-Hungarian Przemyśl Fortress, built to strengthen the strategic fortifications around the city of Przemyśl in present-day Poland.
E1944355 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: Fort XXXV Borek | Statement: [Przemyśl Fortress, hasPart, Fort XXXV Borek]
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: Fort XXXV Borek
Triple: [Przemyśl Fortress, hasPart, Fort XXXV Borek]
Generated description
Fort XXXV Borek is one of the defensive works of the Austro-Hungarian Przemyśl Fortress, built to strengthen the strategic fortifications around the city of Przemyśl in present-day Poland.

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_69f224ca2fa881908a3ac5fedf207b90 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f694fd057481909ab6d876754c59c5 completed May 3, 2026, 12:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a292b0cc6b481908e17142e16a68a60 completed June 10, 2026, 9:14 a.m.
NEDg Description generation batch_6a292c0292c48190b984beebb9754aca completed June 10, 2026, 9:18 a.m.
NED2 Entity disambiguation (via description) batch_6a292cc4074c8190ad11b0dde89b515f completed June 10, 2026, 9:22 a.m.
Created at: April 29, 2026, 8:59 p.m.