Triple
T17150222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Seu d’Urgell |
E416199
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object |
Sort
Sort is a small town in the Catalan Pyrenees of northeastern Spain, known as a gateway to mountain landscapes and outdoor activities.
|
E1252090
|
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: Sort | Statement: [La Seu d’Urgell, near, Sort]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sort Context triple: [La Seu d’Urgell, near, Sort]
-
A.
MatSort
MatSort is an Angular Material directive that adds sorting capabilities to data tables and other collections by managing and emitting sort state changes.
-
B.
Sortu
Sortu is a left-wing Basque nationalist political party that advocates for Basque self-determination and social justice.
-
C.
Tarea Ordenamiento
Tarea Ordenamiento was a major Cuban economic reform program that eliminated the dual-currency system, devalued the peso, and overhauled wages, prices, and subsidies starting in 2021.
-
D.
Sortlending
Sortlending is the Norwegian demonym for inhabitants of the town and municipality of Sortland in Nordland county, Norway.
-
E.
Merge sort
Merge sort is a comparison-based, divide-and-conquer sorting algorithm that recursively splits a list into halves, sorts them, and then merges the sorted halves into a fully ordered sequence.
- 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: Sort Triple: [La Seu d’Urgell, near, Sort]
Generated description
Sort is a small town in the Catalan Pyrenees of northeastern Spain, known as a gateway to mountain landscapes and outdoor activities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sort Target entity description: Sort is a small town in the Catalan Pyrenees of northeastern Spain, known as a gateway to mountain landscapes and outdoor activities.
-
A.
MatSort
MatSort is an Angular Material directive that adds sorting capabilities to data tables and other collections by managing and emitting sort state changes.
-
B.
Sortu
Sortu is a left-wing Basque nationalist political party that advocates for Basque self-determination and social justice.
-
C.
Tarea Ordenamiento
Tarea Ordenamiento was a major Cuban economic reform program that eliminated the dual-currency system, devalued the peso, and overhauled wages, prices, and subsidies starting in 2021.
-
D.
Sortlending
Sortlending is the Norwegian demonym for inhabitants of the town and municipality of Sortland in Nordland county, Norway.
-
E.
Merge sort
Merge sort is a comparison-based, divide-and-conquer sorting algorithm that recursively splits a list into halves, sorts them, and then merges the sorted halves into a fully ordered sequence.
- 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_69d886d279c081909f8ff1f743ddeb69 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f4067470819084aa233c4c4a6d4f |
completed | April 18, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01415b1d7c81908d000b0362042687 |
completed | May 11, 2026, 2:39 a.m. |
| NEDg | Description generation | batch_6a0141b73e008190be8aa85dec1ba517 |
completed | May 11, 2026, 2:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01421d159c819096efc46fa08a48b9 |
completed | May 11, 2026, 2:42 a.m. |
Created at: April 10, 2026, 5:36 a.m.