Triple
T13239275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gironès |
E315236
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Viladasens
Viladasens is a small rural municipality in the province of Girona, Catalonia, known for its agricultural landscape and traditional Catalan village character.
|
E1028487
|
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: Viladasens | Statement: [Gironès, contains, Viladasens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viladasens Context triple: [Gironès, contains, Viladasens]
-
A.
Viddalba
Viddalba is a small town and comune in northern Sardinia, Italy, known for its rural setting and proximity to the Gallura region’s coastal and archaeological attractions.
-
B.
Svaliava
Svaliava is a small town in western Ukraine known for its scenic Carpathian surroundings and mineral springs.
-
C.
Veitvet
Veitvet is a residential neighborhood in Oslo, Norway, known for its apartment blocks, local shopping center, and multicultural community.
-
D.
Liausson
Liausson is a small commune in southern France’s Hérault department, known for its scenic setting on the shores of the artificial Lac du Salagou.
-
E.
Verchota
Verchota is a surname most notably associated with Phil Verchota, an American ice hockey player and member of the 1980 "Miracle on Ice" U.S. Olympic team.
- 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: Viladasens Triple: [Gironès, contains, Viladasens]
Generated description
Viladasens is a small rural municipality in the province of Girona, Catalonia, known for its agricultural landscape and traditional Catalan village character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Viladasens Target entity description: Viladasens is a small rural municipality in the province of Girona, Catalonia, known for its agricultural landscape and traditional Catalan village character.
-
A.
Viddalba
Viddalba is a small town and comune in northern Sardinia, Italy, known for its rural setting and proximity to the Gallura region’s coastal and archaeological attractions.
-
B.
Svaliava
Svaliava is a small town in western Ukraine known for its scenic Carpathian surroundings and mineral springs.
-
C.
Veitvet
Veitvet is a residential neighborhood in Oslo, Norway, known for its apartment blocks, local shopping center, and multicultural community.
-
D.
Liausson
Liausson is a small commune in southern France’s Hérault department, known for its scenic setting on the shores of the artificial Lac du Salagou.
-
E.
Verchota
Verchota is a surname most notably associated with Phil Verchota, an American ice hockey player and member of the 1980 "Miracle on Ice" U.S. Olympic team.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d5850ac8190849a51da39efe5be |
completed | April 10, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff323a3c8190b46b24e69e653105 |
completed | May 3, 2026, 7:54 a.m. |
| NEDg | Description generation | batch_69f7013b3428819083c2bb6032aa08d4 |
completed | May 3, 2026, 8:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f702b40f088190bc3c24321309dfb1 |
completed | May 3, 2026, 8:09 a.m. |
Created at: April 9, 2026, 9:23 p.m.