Triple
T10701509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teplice nad Metují |
E252287
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Javor
Javor is a locality or settlement that forms part of the town of Teplice nad Metují in the Hradec Králové Region of the Czech Republic.
|
E880237
|
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: Javor | Statement: [Teplice nad Metují, hasPart, Javor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Javor Context triple: [Teplice nad Metují, hasPart, Javor]
-
A.
Jurjev
Jurjev is a historical name for the Estonian city of Tartu, reflecting its past under various regional powers.
-
B.
Vukovica
Vukovica is the standardized orthography of the Serbo-Croatian language based on the phonemic spelling principles codified by linguist Vuk Karadžić.
-
C.
Morača
Morača is a major river in Montenegro that flows through the capital city of Podgorica before emptying into Lake Skadar.
-
D.
Ilijaš
Ilijaš is a town and municipality in central Bosnia and Herzegovina, situated northwest of Sarajevo and known for its industrial heritage and surrounding hilly landscape.
-
E.
Velenjak
Velenjak is an affluent residential and cultural neighborhood in northern Tehran, known for its proximity to the Alborz mountains and several major universities.
- 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: Javor Triple: [Teplice nad Metují, hasPart, Javor]
Generated description
Javor is a locality or settlement that forms part of the town of Teplice nad Metují in the Hradec Králové Region of the Czech Republic.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Javor Target entity description: Javor is a locality or settlement that forms part of the town of Teplice nad Metují in the Hradec Králové Region of the Czech Republic.
-
A.
Jurjev
Jurjev is a historical name for the Estonian city of Tartu, reflecting its past under various regional powers.
-
B.
Vukovica
Vukovica is the standardized orthography of the Serbo-Croatian language based on the phonemic spelling principles codified by linguist Vuk Karadžić.
-
C.
Morača
Morača is a major river in Montenegro that flows through the capital city of Podgorica before emptying into Lake Skadar.
-
D.
Ilijaš
Ilijaš is a town and municipality in central Bosnia and Herzegovina, situated northwest of Sarajevo and known for its industrial heritage and surrounding hilly landscape.
-
E.
Velenjak
Velenjak is an affluent residential and cultural neighborhood in northern Tehran, known for its proximity to the Alborz mountains and several major universities.
- 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_69d6aa5cbabc8190973e683950d89faf |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fd8c835c8190bf1a67ee94195926 |
completed | April 9, 2026, 1:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d998f5cda081909932daa3c98f8b46 |
completed | April 11, 2026, 12:42 a.m. |
| NEDg | Description generation | batch_69d99e8534688190b312b737e0b9cd53 |
completed | April 11, 2026, 1:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69da625a1e8c8190b282e7a70bb7c876 |
completed | April 11, 2026, 3:01 p.m. |
Created at: April 8, 2026, 9:12 p.m.