Triple
T13314458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seu Vella cathedral |
E317153
|
entity |
| Predicate | localName |
P657
|
FINISHED |
| Object |
Seu Vella
Seu Vella is a historic hilltop cathedral and iconic landmark overlooking the city of Lleida in Catalonia, Spain.
|
E1033489
|
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: Seu Vella | Statement: [Seu Vella cathedral, localName, Seu Vella]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seu Vella Context triple: [Seu Vella cathedral, localName, Seu Vella]
-
A.
Velia Titta
Velia Titta was the wife of Italian socialist politician Giacomo Matteotti, who became a symbol of resistance after his assassination by Fascist squads in 1924.
-
B.
Elviro
Elviro is a comic servant character from George Frideric Handel’s opera "Serse," known for his humorous disguises and light-hearted scenes.
-
C.
Balvín
Balvín is a Spanish-language surname most notably associated with Colombian reggaeton singer J Balvin (José Álvaro Osorio Balvín).
-
D.
Livaneli
Livaneli is the surname of Zülfü Livaneli, a prominent Turkish musician, novelist, and political figure.
-
E.
Vosso
Vosso is a river in western Norway known for flowing through Voss municipality and contributing to the region’s scenic fjord landscape.
- 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: Seu Vella Triple: [Seu Vella cathedral, localName, Seu Vella]
Generated description
Seu Vella is a historic hilltop cathedral and iconic landmark overlooking the city of Lleida in Catalonia, Spain.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Seu Vella Target entity description: Seu Vella is a historic hilltop cathedral and iconic landmark overlooking the city of Lleida in Catalonia, Spain.
-
A.
Velia Titta
Velia Titta was the wife of Italian socialist politician Giacomo Matteotti, who became a symbol of resistance after his assassination by Fascist squads in 1924.
-
B.
Elviro
Elviro is a comic servant character from George Frideric Handel’s opera "Serse," known for his humorous disguises and light-hearted scenes.
-
C.
Balvín
Balvín is a Spanish-language surname most notably associated with Colombian reggaeton singer J Balvin (José Álvaro Osorio Balvín).
-
D.
Livaneli
Livaneli is the surname of Zülfü Livaneli, a prominent Turkish musician, novelist, and political figure.
-
E.
Vosso
Vosso is a river in western Norway known for flowing through Voss municipality and contributing to the region’s scenic fjord landscape.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d990f8a86481909ea2942c63037b77 |
completed | April 11, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716ec2ec08190a6e37795b422fe71 |
completed | May 3, 2026, 9:35 a.m. |
| NEDg | Description generation | batch_69f717d953b48190954b86c41ff34c07 |
completed | May 3, 2026, 9:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f718b852808190a2a0fb48424bffb0 |
completed | May 3, 2026, 9:43 a.m. |
Created at: April 9, 2026, 9:29 p.m.