Triple
T10041195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College of Europe |
E205298
|
entity |
| Predicate | hasCampusIn |
P4623
|
FINISHED |
| Object |
Natolin
Natolin is a district in Warsaw, Poland, known for hosting one of the two campuses of the College of Europe, specializing in European studies.
|
E836917
|
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: Natolin | Statement: [College of Europe, hasCampusIn, Natolin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Natolin Context triple: [College of Europe, hasCampusIn, Natolin]
-
A.
Tykocin
Tykocin is a historic town in northeastern Poland known for its well-preserved Jewish heritage, baroque architecture, and role in Polish royal and noble history.
-
B.
Latimore
Latimore is a surname most notably associated with American actor and R&B singer Jacob Latimore.
-
C.
Dolo
Dolo is an Italian stream that serves as a tributary of the Secchia River in northern Italy.
-
D.
Durolle
Durolle is a river in central France that flows through the town of Thiers, historically powering its renowned cutlery and knife-making industry.
-
E.
Tartegnin
Tartegnin is a small wine-producing municipality in the canton of Vaud in western Switzerland, situated above Lake Geneva in the La Côte 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: Natolin Triple: [College of Europe, hasCampusIn, Natolin]
Generated description
Natolin is a district in Warsaw, Poland, known for hosting one of the two campuses of the College of Europe, specializing in European studies.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Natolin Target entity description: Natolin is a district in Warsaw, Poland, known for hosting one of the two campuses of the College of Europe, specializing in European studies.
-
A.
Tykocin
Tykocin is a historic town in northeastern Poland known for its well-preserved Jewish heritage, baroque architecture, and role in Polish royal and noble history.
-
B.
Latimore
Latimore is a surname most notably associated with American actor and R&B singer Jacob Latimore.
-
C.
Dolo
Dolo is an Italian stream that serves as a tributary of the Secchia River in northern Italy.
-
D.
Durolle
Durolle is a river in central France that flows through the town of Thiers, historically powering its renowned cutlery and knife-making industry.
-
E.
Tartegnin
Tartegnin is a small wine-producing municipality in the canton of Vaud in western Switzerland, situated above Lake Geneva in the La Côte 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_69ca834f70e88190b2d74828b7767ec1 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcee2e6d881908cfa0579f9be32e4 |
completed | April 2, 2026, 2:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2827064108190b9079717a4eb98d6 |
completed | April 5, 2026, 3:40 p.m. |
| NEDg | Description generation | batch_69d2834f6d488190812f91a5b4971c1e |
completed | April 5, 2026, 3:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d28432d900819091ff0d324a6bb28a |
completed | April 5, 2026, 3:48 p.m. |
Created at: March 30, 2026, 8:55 p.m.