Triple
T16199751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zličín |
E393165
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object |
Řepy
Řepy is a residential district in the western part of Prague, Czech Republic, known for its large housing estates and proximity to major transport routes.
|
E1198651
|
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: Řepy | Statement: [Zličín, locatedNear, Řepy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Řepy Context triple: [Zličín, locatedNear, Řepy]
-
A.
Mokřiny
Mokřiny is a village and administrative part of the town of Aš in the Karlovy Vary Region of the Czech Republic.
-
B.
Podyjí
Podyjí is a protected national park area in the Czech Republic known for its deep Dyje River valley, diverse ecosystems, and well-preserved natural landscapes.
-
C.
Letňany
Letňany is a district in the northeastern part of Prague, Czech Republic, known for its residential areas, shopping centers, and transport links including a terminus of the city’s metro system.
-
D.
Rokytne
Rokytne is a Ukrainian urban locality situated along the Ros River, known as a small regional center in central Ukraine.
-
E.
Šurany
Šurany is a small town in southwestern Slovakia known for its agricultural surroundings and historical roots in the Nitra region.
- 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: Řepy Triple: [Zličín, locatedNear, Řepy]
Generated description
Řepy is a residential district in the western part of Prague, Czech Republic, known for its large housing estates and proximity to major transport routes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Řepy Target entity description: Řepy is a residential district in the western part of Prague, Czech Republic, known for its large housing estates and proximity to major transport routes.
-
A.
Mokřiny
Mokřiny is a village and administrative part of the town of Aš in the Karlovy Vary Region of the Czech Republic.
-
B.
Podyjí
Podyjí is a protected national park area in the Czech Republic known for its deep Dyje River valley, diverse ecosystems, and well-preserved natural landscapes.
-
C.
Letňany
Letňany is a district in the northeastern part of Prague, Czech Republic, known for its residential areas, shopping centers, and transport links including a terminus of the city’s metro system.
-
D.
Rokytne
Rokytne is a Ukrainian urban locality situated along the Ros River, known as a small regional center in central Ukraine.
-
E.
Šurany
Šurany is a small town in southwestern Slovakia known for its agricultural surroundings and historical roots in the Nitra region.
- 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_69d87f1f5bd08190bd01cac0d5b9d2ef |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e222de2db481908471b9c73d444607 |
completed | April 17, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffff1107908190afda091b53317d81 |
completed | May 10, 2026, 3:44 a.m. |
| NEDg | Description generation | batch_6a00014d982881908dcb9a0abd75a1e2 |
completed | May 10, 2026, 3:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00021e42ec8190af9869b7f8be3ce5 |
completed | May 10, 2026, 3:57 a.m. |
Created at: April 10, 2026, 5:03 a.m.