Triple

T5789705
Position Surface form Disambiguated ID Type / Status
Subject Low Beskids E128361 entity
Predicate hasHighestPoint P210 FINISHED
Object Lackowa
Lackowa is a prominent mountain peak in the Low Beskids range on the Polish-Slovak border, known for its forested slopes and scenic hiking routes.
E549378 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: Lackowa | Statement: [Low Beskids, hasHighestPoint, Lackowa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lackowa
Context triple: [Low Beskids, hasHighestPoint, Lackowa]
  • A. Muszyna
    Muszyna is a spa and tourist town in southern Poland, known for its mineral springs and scenic mountain surroundings near the Slovak border.
  • B. Bystra
    Bystra is a prominent peak in the Western Tatras, known as the highest summit on the Slovak side of this mountain range.
  • C. Markusy
    Markusy is a village in northern Poland located in the Warmian-Masurian Voivodeship.
  • D. Ciecere
    Ciecere is a river in western Latvia that serves as one of the tributaries of the Venta River.
  • E. Ciechocinek
    Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
  • 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: Lackowa
Triple: [Low Beskids, hasHighestPoint, Lackowa]
Generated description
Lackowa is a prominent mountain peak in the Low Beskids range on the Polish-Slovak border, known for its forested slopes and scenic hiking routes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lackowa
Target entity description: Lackowa is a prominent mountain peak in the Low Beskids range on the Polish-Slovak border, known for its forested slopes and scenic hiking routes.
  • A. Muszyna
    Muszyna is a spa and tourist town in southern Poland, known for its mineral springs and scenic mountain surroundings near the Slovak border.
  • B. Bystra
    Bystra is a prominent peak in the Western Tatras, known as the highest summit on the Slovak side of this mountain range.
  • C. Markusy
    Markusy is a village in northern Poland located in the Warmian-Masurian Voivodeship.
  • D. Ciecere
    Ciecere is a river in western Latvia that serves as one of the tributaries of the Venta River.
  • E. Ciechocinek
    Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
  • 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_69c0084450048190bc647b649a05136b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02a5585788190821b8da40259e0e7 completed March 22, 2026, 5:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0981d9430819081e953dba9c2f8f8 completed March 23, 2026, 1:32 a.m.
NEDg Description generation batch_69c0989f7e58819098175e6eaacdb9ee completed March 23, 2026, 1:34 a.m.
NED2 Entity disambiguation (via description) batch_69c09cf3220481908c52b519e8495fff completed March 23, 2026, 1:52 a.m.
Created at: March 22, 2026, 3:51 p.m.