Triple
T14402403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Customs of Finland |
E357103
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object |
Tulli
Tulli is the Finnish Customs authority responsible for overseeing customs control, collecting duties and taxes, and facilitating international trade in Finland.
|
E1097384
|
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: Tulli | Statement: [Customs of Finland, nativeName, Tulli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tulli Context triple: [Customs of Finland, nativeName, Tulli]
-
A.
Maenza
Maenza is a small historic town in the Lazio region of central Italy, known for its medieval architecture and hilltop setting.
-
B.
Tullio
Tullio is an Italian given name most famously borne by the mathematician Tullio Levi-Civita, known for his work in tensor calculus and differential geometry.
-
C.
Delle
Delle is a small commune in northeastern France near the Swiss border, known as a local administrative and economic center in the Territoire de Belfort department.
-
D.
Tull
Tull is a surname most prominently associated with American film producer and entrepreneur Thomas Tull.
-
E.
Statilia
Statilia is an ancient Roman feminine praenomen (given name) most notably borne by the empress Statilia Messalina, wife of Emperor Nero.
- 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: Tulli Triple: [Customs of Finland, nativeName, Tulli]
Generated description
Tulli is the Finnish Customs authority responsible for overseeing customs control, collecting duties and taxes, and facilitating international trade in Finland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tulli Target entity description: Tulli is the Finnish Customs authority responsible for overseeing customs control, collecting duties and taxes, and facilitating international trade in Finland.
-
A.
Maenza
Maenza is a small historic town in the Lazio region of central Italy, known for its medieval architecture and hilltop setting.
-
B.
Tullio
Tullio is an Italian given name most famously borne by the mathematician Tullio Levi-Civita, known for his work in tensor calculus and differential geometry.
-
C.
Delle
Delle is a small commune in northeastern France near the Swiss border, known as a local administrative and economic center in the Territoire de Belfort department.
-
D.
Tull
Tull is a surname most prominently associated with American film producer and entrepreneur Thomas Tull.
-
E.
Statilia
Statilia is an ancient Roman feminine praenomen (given name) most notably borne by the empress Statilia Messalina, wife of Emperor Nero.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de908500048190bb6a20fe318d5c62 |
completed | April 14, 2026, 7:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5520c07c8190bfdaf224dd779ced |
completed | May 8, 2026, 3:14 a.m. |
| NEDg | Description generation | batch_69fd56bbd6e481909fd97f3808bc99fd |
completed | May 8, 2026, 3:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd5755156c8190bc27df83e940c403 |
completed | May 8, 2026, 3:24 a.m. |
Created at: April 10, 2026, 1:17 a.m.