Triple

T26057685
Position Surface form Disambiguated ID Type / Status
Subject Yamburg (Kingisepp) E657166 entity
Predicate hasFortification P8412 FINISHED
Object Yamburg fortress
Yamburg fortress was a historic Russian stronghold located in what is now Kingisepp, serving as a strategic defensive fortification in the northwest of the country.
E1709294 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: Yamburg fortress | Statement: [Yamburg (Kingisepp), hasFortification, Yamburg fortress]
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: Yamburg fortress
Triple: [Yamburg (Kingisepp), hasFortification, Yamburg fortress]
Generated description
Yamburg fortress was a historic Russian stronghold located in what is now Kingisepp, serving as a strategic defensive fortification in the northwest of the country.

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_69ee5bbd788481909e22bd7153d0c037 completed April 26, 2026, 6:38 p.m.
NER Named-entity recognition batch_69f6068fa9708190a061497990b64cd4 completed May 2, 2026, 2:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a111b2372488190a0a87e762e5000cb completed May 23, 2026, 3:12 a.m.
NEDg Description generation batch_6a111f06ca1c8190a5e50097f6b910fd completed May 23, 2026, 3:29 a.m.
NED2 Entity disambiguation (via description) batch_6a111fb122748190b9487873be677c5c completed May 23, 2026, 3:32 a.m.
Created at: April 26, 2026, 7:12 p.m.