Triple
T12042183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tachov District |
E286688
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Lestkov
Lestkov is a small municipality and village located in the Tachov District of the Plzeň Region in the Czech Republic.
|
E963108
|
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: Lestkov | Statement: [Tachov District, contains, Lestkov]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lestkov Context triple: [Tachov District, contains, Lestkov]
-
A.
Kologriv
Kologriv is a small historic town in Kostroma Oblast, Russia, known for its traditional wooden architecture and location within a forested, sparsely populated region.
-
B.
Vyazemsky
Vyazemsky is a small town in Russia’s Far Eastern Federal District, serving as an administrative center within Khabarovsk Krai.
-
C.
Yuryatin
Yuryatin is a fictional Russian town in Boris Pasternak’s novel "Doctor Zhivago," serving as a key setting in Lara Antipova’s story.
-
D.
Khovrino
Khovrino is a Moscow Metro station serving as the northern terminus of the Zamoskvoretskaya Line.
-
E.
Khokhlov
Khokhlov is a Russian surname commonly found in Eastern Europe, typically indicating Slavic heritage.
- 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: Lestkov Triple: [Tachov District, contains, Lestkov]
Generated description
Lestkov is a small municipality and village located in the Tachov District of the Plzeň Region in the Czech Republic.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lestkov Target entity description: Lestkov is a small municipality and village located in the Tachov District of the Plzeň Region in the Czech Republic.
-
A.
Kologriv
Kologriv is a small historic town in Kostroma Oblast, Russia, known for its traditional wooden architecture and location within a forested, sparsely populated region.
-
B.
Vyazemsky
Vyazemsky is a small town in Russia’s Far Eastern Federal District, serving as an administrative center within Khabarovsk Krai.
-
C.
Yuryatin
Yuryatin is a fictional Russian town in Boris Pasternak’s novel "Doctor Zhivago," serving as a key setting in Lara Antipova’s story.
-
D.
Khovrino
Khovrino is a Moscow Metro station serving as the northern terminus of the Zamoskvoretskaya Line.
-
E.
Khokhlov
Khokhlov is a Russian surname commonly found in Eastern Europe, typically indicating Slavic heritage.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9040d13108190bd1a969fa62aae5a |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f649dbf081908e76c45e362217c1 |
completed | May 2, 2026, 1:04 p.m. |
| NEDg | Description generation | batch_69f5fc5d6d808190ba96e08fd7d1f045 |
completed | May 2, 2026, 1:30 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f5fd149d9c8190a9d6e021801632d4 |
completed | May 2, 2026, 1:33 p.m. |
Created at: April 8, 2026, 9:47 p.m.