Triple
T21152250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madrid skyline |
E521220
|
entity |
| Predicate | includesLandmark |
P22581
|
FINISHED |
| Object |
Torrespaña
Torrespaña is a prominent telecommunications tower and broadcasting landmark that dominates the skyline of Madrid, Spain.
|
E1470651
|
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: Torrespaña | Statement: [Madrid skyline, includesLandmark, Torrespaña]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Torrespaña Context triple: [Madrid skyline, includesLandmark, Torrespaña]
-
A.
Capalonga
Capalonga is a coastal municipality in the Philippine province of Camarines Norte known for its fishing communities, natural attractions, and religious pilgrimage sites.
-
B.
Tordera
Tordera is a municipality in the Maresme comarca of Catalonia, Spain, known for its rural landscapes and proximity to the Costa Brava.
-
C.
Torredembarra
Torredembarra is a coastal town in Catalonia, Spain, known for its Mediterranean beaches, historic old quarter, and well-preserved lighthouse.
-
D.
Osuna
Osuna is a historic town in the province of Seville, Spain, known for its rich archaeological heritage, including notable ancient reliefs and other Roman-era remains.
-
E.
Coaña
Coaña is a coastal municipality in the Asturias region of northern Spain, known for its prehistoric hillfort (castro) and rural landscapes.
- 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: Torrespaña Triple: [Madrid skyline, includesLandmark, Torrespaña]
Generated description
Torrespaña is a prominent telecommunications tower and broadcasting landmark that dominates the skyline of Madrid, Spain.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Torrespaña Target entity description: Torrespaña is a prominent telecommunications tower and broadcasting landmark that dominates the skyline of Madrid, Spain.
-
A.
Capalonga
Capalonga is a coastal municipality in the Philippine province of Camarines Norte known for its fishing communities, natural attractions, and religious pilgrimage sites.
-
B.
Tordera
Tordera is a municipality in the Maresme comarca of Catalonia, Spain, known for its rural landscapes and proximity to the Costa Brava.
-
C.
Torredembarra
Torredembarra is a coastal town in Catalonia, Spain, known for its Mediterranean beaches, historic old quarter, and well-preserved lighthouse.
-
D.
Osuna
Osuna is a historic town in the province of Seville, Spain, known for its rich archaeological heritage, including notable ancient reliefs and other Roman-era remains.
-
E.
Coaña
Coaña is a coastal municipality in the Asturias region of northern Spain, known for its prehistoric hillfort (castro) and rural landscapes.
- 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_69e0b50c6a848190a4e525a77a319b8a |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7240275b481908748c0e3f187ed34 |
completed | April 21, 2026, 7:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a097569a3d481908b71593d2309f3b0 |
completed | May 17, 2026, 7:59 a.m. |
| NEDg | Description generation | batch_6a097704c6a881908008357c86d75f3d |
completed | May 17, 2026, 8:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09775da35081909628417a2859655d |
completed | May 17, 2026, 8:07 a.m. |
Created at: April 16, 2026, 2:58 p.m.