Triple
T17612533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cisna |
E428996
|
entity |
| Predicate | roadAccessFrom |
P22549
|
FINISHED |
| Object |
Lesko
Lesko is a small town in southeastern Poland, often considered a gateway to the Bieszczady Mountains and known for its historic architecture and scenic surroundings.
|
E1278351
|
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: Lesko | Statement: [Cisna, roadAccessFrom, Lesko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lesko Context triple: [Cisna, roadAccessFrom, Lesko]
-
A.
Olesko
Olesko is a historic town in western Ukraine best known for its medieval castle, which served as the birthplace of Polish King John III Sobieski.
-
B.
Mahlberg
Mahlberg is a small town and municipality in the Ortenau district of Baden-Württemberg in southwestern Germany.
-
C.
Lohrberg
Lohrberg is a hill in Germany’s Siebengebirge range, known for its forested slopes and scenic hiking paths overlooking the Rhine valley.
-
D.
Lohrberg
Lohrberg is a hill and popular recreational area in Frankfurt am Main, known for its vineyards, panoramic city views, and green spaces.
-
E.
Weitzel
Weitzel is a surname of likely German or Dutch origin borne by individuals such as Edu Weitzel Douwes Dekker.
- 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: Lesko Triple: [Cisna, roadAccessFrom, Lesko]
Generated description
Lesko is a small town in southeastern Poland, often considered a gateway to the Bieszczady Mountains and known for its historic architecture and scenic surroundings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lesko Target entity description: Lesko is a small town in southeastern Poland, often considered a gateway to the Bieszczady Mountains and known for its historic architecture and scenic surroundings.
-
A.
Olesko
Olesko is a historic town in western Ukraine best known for its medieval castle, which served as the birthplace of Polish King John III Sobieski.
-
B.
Mahlberg
Mahlberg is a small town and municipality in the Ortenau district of Baden-Württemberg in southwestern Germany.
-
C.
Lohrberg
Lohrberg is a hill in Germany’s Siebengebirge range, known for its forested slopes and scenic hiking paths overlooking the Rhine valley.
-
D.
Lohrberg
Lohrberg is a hill and popular recreational area in Frankfurt am Main, known for its vineyards, panoramic city views, and green spaces.
-
E.
Weitzel
Weitzel is a surname of likely German or Dutch origin borne by individuals such as Edu Weitzel Douwes Dekker.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46d2eaa348190a8226eef8c0d6e31 |
completed | April 19, 2026, 5:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01e8267d388190b97e038e142f338f |
completed | May 11, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_6a01f100fe5c81909bb43e89b60c27df |
completed | May 11, 2026, 3:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01f17a3efc81909404abb3a7ed6523 |
completed | May 11, 2026, 3:10 p.m. |
Created at: April 10, 2026, 5:51 a.m.