Triple

T2207088
Position Surface form Disambiguated ID Type / Status
Subject Marker E50824 entity
Predicate borderWith P224 FINISHED
Object Aremark E50823 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: Aremark | Statement: [Marker, borderWith, Aremark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aremark
Context triple: [Marker, borderWith, Aremark]
  • A. Aremark chosen
    Aremark is a small rural municipality in southeastern Norway known for its forests, lakes, and outdoor recreation.
  • B. Ateste
    Ateste is the ancient name of the Italian town of Este, historically significant as a center of the Venetic civilization in northern Italy.
  • C. Ant
    Ant is a Java-based build automation tool commonly used to compile, package, and deploy Java applications using XML configuration files.
  • D. Auch
    Auch is a historic town in southwestern France that serves as the capital of the Gers department and is known for its cathedral and medieval old town.
  • E. Aha
    Aha is an early Egyptian pharaoh, often identified with the legendary Menes, who is traditionally credited with unifying Upper and Lower Egypt and founding the First Dynasty.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a88b06709c8190978fb2418470d1b6 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abbfcbb83081908d5b2f1603c7b4d2 completed March 7, 2026, 6:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae654b89b081908f8c8b9bfc0b6579 completed March 9, 2026, 6:14 a.m.
Created at: March 4, 2026, 7:46 p.m.