Triple

T27978865
Position Surface form Disambiguated ID Type / Status
Subject Police Medal for Merit E706563 entity
Predicate presentedBy P83 FINISHED
Object Government of Poland
The Government of Poland is the central executive authority of the Republic of Poland, responsible for national administration, public policy, and the implementation and enforcement of laws.
E46573 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: Government of Poland | Statement: [Police Medal for Merit, presentedBy, Government of Poland]
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: Government of Poland
Triple: [Police Medal for Merit, presentedBy, Government of Poland]
Generated description
The Government of Poland is the central executive authority of the Republic of Poland, responsible for national administration, public policy, and the implementation and enforcement of laws.

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_69ef96b7f330819090f315318ba6977e completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69f63b66e9248190974ea3d66f984de1 completed May 2, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a13117a30c88190b0c640bd8a266703 completed May 24, 2026, 2:55 p.m.
NEDg Description generation batch_6a1312b5baf88190a9279556df3173ab completed May 24, 2026, 3:01 p.m.
NED2 Entity disambiguation (via description) batch_6a13133814d48190991b1eaaf1e93bb7 completed May 24, 2026, 3:03 p.m.
Created at: April 27, 2026, 7:43 p.m.