Triple
T17295629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivanovo Oblast |
E419902
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Vichuga
Vichuga is a small industrial town in central Russia known historically for its textile manufacturing.
|
E1261620
|
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: Vichuga | Statement: [Ivanovo Oblast, contains, Vichuga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vichuga Context triple: [Ivanovo Oblast, contains, Vichuga]
-
A.
Vilca
Vilca is a small Andean town in Peru known for its scenic highland landscapes, lagoons, and traditional rural culture within the Nor Yauyos-Cochas reserve.
-
B.
Schivelbein
Schivelbein is a historic town in northwestern Poland, known today as Świdwin, situated within the Rega River basin.
-
C.
Viacha
Viacha is a Bolivian city in the Altiplano region known for its industrial activity and proximity to La Paz.
-
D.
Mürwik
Mürwik is a district of Flensburg in northern Germany, best known for hosting the last seat of the German government at the end of World War II and for its prominent naval academy.
-
E.
Zhadnaya
Zhadnaya is a notable work associated with the celebrated Soviet actress and comedian Faina Ranevskaya.
- 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: Vichuga Triple: [Ivanovo Oblast, contains, Vichuga]
Generated description
Vichuga is a small industrial town in central Russia known historically for its textile manufacturing.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vichuga Target entity description: Vichuga is a small industrial town in central Russia known historically for its textile manufacturing.
-
A.
Vilca
Vilca is a small Andean town in Peru known for its scenic highland landscapes, lagoons, and traditional rural culture within the Nor Yauyos-Cochas reserve.
-
B.
Schivelbein
Schivelbein is a historic town in northwestern Poland, known today as Świdwin, situated within the Rega River basin.
-
C.
Viacha
Viacha is a Bolivian city in the Altiplano region known for its industrial activity and proximity to La Paz.
-
D.
Mürwik
Mürwik is a district of Flensburg in northern Germany, best known for hosting the last seat of the German government at the end of World War II and for its prominent naval academy.
-
E.
Zhadnaya
Zhadnaya is a notable work associated with the celebrated Soviet actress and comedian Faina Ranevskaya.
- 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_69d886db32608190a61e18862c5a8af6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e437875b208190bcf0df2ded546257 |
completed | April 19, 2026, 2:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0180d66bb8819086eb2c72b4dcbafb |
completed | May 11, 2026, 7:10 a.m. |
| NEDg | Description generation | batch_6a01848c84cc8190bbcf1a8be82d0f68 |
completed | May 11, 2026, 7:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01850519108190972c1ecea6b9313c |
completed | May 11, 2026, 7:28 a.m. |
Created at: April 10, 2026, 5:40 a.m.