Triple
T11999978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mogilev Region |
E285632
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Chausy
Chausy is a small town in eastern Belarus known for its historical role in regional trade and its location within the Mogilev Region.
|
E958980
|
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: Chausy | Statement: [Mogilev Region, containsCity, Chausy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chausy Context triple: [Mogilev Region, containsCity, Chausy]
-
A.
Chardonel
Chardonel is a hybrid white wine grape variety known for its cold hardiness and Chardonnay-like character, widely grown in cool-climate American wine regions.
-
B.
de Blainville
de Blainville is the surname of Henri Marie Ducrotay de Blainville, a notable 19th-century French zoologist and anatomist.
-
C.
Capucine
Capucine was a French fashion model and film actress best known for her elegant screen presence in 1960s comedies and dramas, including roles in films like The Pink Panther.
-
D.
Souvestre
Souvestre is a French surname notably borne by educator Marie Souvestre, known for her progressive influence on women’s education in the 19th century.
-
E.
Crompond
Crompond is a small hamlet within the town of Yorktown in Westchester County, New York, known primarily as a residential community.
- 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: Chausy Triple: [Mogilev Region, containsCity, Chausy]
Generated description
Chausy is a small town in eastern Belarus known for its historical role in regional trade and its location within the Mogilev Region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chausy Target entity description: Chausy is a small town in eastern Belarus known for its historical role in regional trade and its location within the Mogilev Region.
-
A.
Chardonel
Chardonel is a hybrid white wine grape variety known for its cold hardiness and Chardonnay-like character, widely grown in cool-climate American wine regions.
-
B.
de Blainville
de Blainville is the surname of Henri Marie Ducrotay de Blainville, a notable 19th-century French zoologist and anatomist.
-
C.
Capucine
Capucine was a French fashion model and film actress best known for her elegant screen presence in 1960s comedies and dramas, including roles in films like The Pink Panther.
-
D.
Souvestre
Souvestre is a French surname notably borne by educator Marie Souvestre, known for her progressive influence on women’s education in the 19th century.
-
E.
Crompond
Crompond is a small hamlet within the town of Yorktown in Westchester County, New York, known primarily as a residential community.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903c26d7881909b67a31d04882eb5 |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f472917ed08190a872d9e5663d5ed5 |
completed | May 1, 2026, 9:29 a.m. |
| NEDg | Description generation | batch_69f47b7e4a40819085680c48eed5418a |
completed | May 1, 2026, 10:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f47df40a8c8190bd7350ba27f57214 |
completed | May 1, 2026, 10:18 a.m. |
Created at: April 8, 2026, 9:46 p.m.