Triple
T18582320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sierra de Gata |
E454144
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Perales del Puerto
Perales del Puerto is a small rural municipality in the Sierra de Gata region of Extremadura, western Spain.
|
E1331854
|
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: Perales del Puerto | Statement: [Sierra de Gata, containsSettlement, Perales del Puerto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Perales del Puerto Context triple: [Sierra de Gata, containsSettlement, Perales del Puerto]
-
A.
Soto de Viñuelas
Soto de Viñuelas is a protected natural area in the Madrid region of Spain, known for its Mediterranean woodlands, wildlife, and role as a peri-urban green space near the Jarama River.
-
B.
Peñuelas
Peñuelas is a municipality on the southern coast of Puerto Rico known for its industrial facilities and proximity to the city of Ponce.
-
C.
Alpuente
Alpuente is a historic town in eastern Spain that once served as the political and administrative center of the medieval Taifa of Alpuente.
-
D.
de Perales
de Perales is a Spanish-language surname most notably associated with Cuban-American beautician and entrepreneur Mirta de Perales.
-
E.
Lo Valledor
Lo Valledor is a metro station on Santiago, Chile’s underground network, serving the city’s Line 6 corridor.
- 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: Perales del Puerto Triple: [Sierra de Gata, containsSettlement, Perales del Puerto]
Generated description
Perales del Puerto is a small rural municipality in the Sierra de Gata region of Extremadura, western Spain.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Perales del Puerto Target entity description: Perales del Puerto is a small rural municipality in the Sierra de Gata region of Extremadura, western Spain.
-
A.
Soto de Viñuelas
Soto de Viñuelas is a protected natural area in the Madrid region of Spain, known for its Mediterranean woodlands, wildlife, and role as a peri-urban green space near the Jarama River.
-
B.
Peñuelas
Peñuelas is a municipality on the southern coast of Puerto Rico known for its industrial facilities and proximity to the city of Ponce.
-
C.
Alpuente
Alpuente is a historic town in eastern Spain that once served as the political and administrative center of the medieval Taifa of Alpuente.
-
D.
de Perales
de Perales is a Spanish-language surname most notably associated with Cuban-American beautician and entrepreneur Mirta de Perales.
-
E.
Lo Valledor
Lo Valledor is a metro station on Santiago, Chile’s underground network, serving the city’s Line 6 corridor.
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e543d10b1c8190a401df810b7290c9 |
completed | April 19, 2026, 9:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a04f88f6870819085ebffc7c77e483f |
completed | May 13, 2026, 10:17 p.m. |
| NEDg | Description generation | batch_6a04f9fc493881909ba9159748d4f3fb |
completed | May 13, 2026, 10:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a04fad8daa88190961d643d30a52aa7 |
completed | May 13, 2026, 10:27 p.m. |
Created at: April 10, 2026, 11:44 a.m.