Triple
T22320532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Blas-Canillejas |
E551770
|
entity |
| Predicate | hasNeighborhood |
P40
|
FINISHED |
| Object |
Rosas
Rosas is a residential neighborhood in the San Blas-Canillejas district of Madrid, Spain, known for its local amenities and urban character.
|
E1531795
|
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: Rosas | Statement: [San Blas-Canillejas, hasNeighborhood, Rosas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rosas Context triple: [San Blas-Canillejas, hasNeighborhood, Rosas]
-
A.
Ellacuría
Ellacuría is a Basque-origin surname most notably associated with Ignacio Ellacuría, a Spanish-Salvadoran Jesuit priest, philosopher, and prominent liberation theologian.
-
B.
de Villarroel
de Villarroel is a Spanish surname historically associated with military and noble lineages, notably including officers in the armies of the Spanish monarchy.
-
C.
Rivadavia
Rivadavia is a Spanish-language surname most notably associated with Argentine statesman and first president Bernardino Rivadavia.
-
D.
Gastón
Gastón is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
-
E.
Rojas
Rojas is a Spanish surname historically associated with prominent noble families and political figures in Spain.
- 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: Rosas Triple: [San Blas-Canillejas, hasNeighborhood, Rosas]
Generated description
Rosas is a residential neighborhood in the San Blas-Canillejas district of Madrid, Spain, known for its local amenities and urban character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rosas Target entity description: Rosas is a residential neighborhood in the San Blas-Canillejas district of Madrid, Spain, known for its local amenities and urban character.
-
A.
Ellacuría
Ellacuría is a Basque-origin surname most notably associated with Ignacio Ellacuría, a Spanish-Salvadoran Jesuit priest, philosopher, and prominent liberation theologian.
-
B.
de Villarroel
de Villarroel is a Spanish surname historically associated with military and noble lineages, notably including officers in the armies of the Spanish monarchy.
-
C.
Rivadavia
Rivadavia is a Spanish-language surname most notably associated with Argentine statesman and first president Bernardino Rivadavia.
-
D.
Gastón
Gastón is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
-
E.
Rojas
Rojas is a Spanish surname historically associated with prominent noble families and political figures in Spain.
- 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_69e11e4776588190abb21e5cea79973f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15763bf0881908d859f85b4a6ce28 |
completed | April 29, 2026, 12:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ad51a87688190ad638880953172c7 |
completed | May 18, 2026, 9 a.m. |
| NEDg | Description generation | batch_6a0ad991a1e48190ad240a20694223fc |
completed | May 18, 2026, 9:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ada2a61b881908a636b2d1d6e4509 |
completed | May 18, 2026, 9:21 a.m. |
Created at: April 16, 2026, 8:42 p.m.