Triple

T21514150
Position Surface form Disambiguated ID Type / Status
Subject Mierzeja Wiślana E530800 entity
Predicate hasSettlement P1068 FINISHED
Object Mikoszewo
Mikoszewo is a small coastal village in northern Poland situated at the mouth of the Vistula River on the Vistula Spit.
E1852343 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: Mikoszewo | Statement: [Mierzeja Wiślana, hasSettlement, Mikoszewo]
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: Mikoszewo
Triple: [Mierzeja Wiślana, hasSettlement, Mikoszewo]
Generated description
Mikoszewo is a small coastal village in northern Poland situated at the mouth of the Vistula River on the Vistula Spit.

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_69e0c45c81f08190a6b8bbb70a45aae7 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea88e6fc8190a4b73b8d32dae5a8 completed April 23, 2026, 9:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2550275dfc8190a49811931904c7f6 completed June 7, 2026, 11:04 a.m.
NEDg Description generation batch_6a2554568f388190960bbfb09ed37b1d completed June 7, 2026, 11:21 a.m.
NED2 Entity disambiguation (via description) batch_6a2558e69dfc81908eea54a231ab38e7 completed June 7, 2026, 11:41 a.m.
Created at: April 16, 2026, 6:25 p.m.