Triple

T16684134
Position Surface form Disambiguated ID Type / Status
Subject Ohře Valley E405414 entity
Predicate contains P35 FINISHED
Object Loket
Loket is a historic Czech town renowned for its medieval castle and picturesque setting on a bend of the Ohře River.
 E1228315 NE FINISHED

How this triple was built (4 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: Loket | Statement: [Ohře Valley, contains, Loket]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Loket
Context triple: [Ohře Valley, contains, Loket]
  • A. Loža
    Loža is the Slovene name for the historic Loggia Palace, a notable civic building and landmark in Koper, Slovenia.
  • B. Lages
    Lages is a city in southern Brazil known for its cattle ranching heritage and cool, highland climate.
  • C. Lvovna
    Lvovna is a Russian patronymic derived from the male given name Lev, traditionally used as the middle name for daughters of men named Lev.
  • D. Lochkov
    Lochkov is a district in Prague, Czech Republic, historically known for its geological significance and giving its name to the Lochkovian stage of the Devonian period.
  • E. Parkano
    Parkano is a small town and municipality in the Pirkanmaa region of western Finland, known for its forests, lakes, and position along key transport routes.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Loket
Triple: [Ohře Valley, contains, Loket]
Generated description
Loket is a historic Czech town renowned for its medieval castle and picturesque setting on a bend of the Ohře River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Loket
Target entity description: Loket is a historic Czech town renowned for its medieval castle and picturesque setting on a bend of the Ohře River.
  • A. Loža
    Loža is the Slovene name for the historic Loggia Palace, a notable civic building and landmark in Koper, Slovenia.
  • B. Lages
    Lages is a city in southern Brazil known for its cattle ranching heritage and cool, highland climate.
  • C. Lvovna
    Lvovna is a Russian patronymic derived from the male given name Lev, traditionally used as the middle name for daughters of men named Lev.
  • D. Lochkov
    Lochkov is a district in Prague, Czech Republic, historically known for its geological significance and giving its name to the Lochkovian stage of the Devonian period.
  • E. Parkano
    Parkano is a small town and municipality in the Pirkanmaa region of western Finland, known for its forests, lakes, and position along key transport routes.
  • F. None of above. chosen

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_69d8838c28748190b3f5967c743940ab completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37d71a66881908c8d06cc074fdf29 completed April 18, 2026, 12:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a008a422f8c8190873fd7089df8fbd4 completed May 10, 2026, 1:38 p.m.
NEDg Description generation batch_6a008b41a1648190bd1c2268c8a80ee2 completed May 10, 2026, 1:42 p.m.
NED2 Entity disambiguation (via description) batch_6a008c2bcac48190801ba34fde104a8a completed May 10, 2026, 1:46 p.m.
Created at: April 10, 2026, 5:19 a.m.