Triple
T3609038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beira Litoral |
E76438
|
entity |
| Predicate | historicalRegion |
P915
|
FINISHED |
| Object |
Beiras
Beiras is a traditional region in central Portugal known for its diverse landscapes, historic cities, and cultural heritage.
|
E374222
|
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: Beiras | Statement: [Beira Litoral, historicalRegion, Beiras]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beiras Context triple: [Beira Litoral, historicalRegion, Beiras]
-
A.
Ribera
Ribera was a prominent 17th-century Spanish Baroque painter, known for his dramatic use of light and shadow and intense religious and genre scenes.
-
B.
Nalón
The Nalón is a major river in Asturias, northern Spain, known for flowing through mountainous landscapes and historically supporting regional industry and mining.
-
C.
Cosío
Cosío is a small municipality and town located in the northern part of the Mexican state of Aguascalientes.
-
D.
Breña Baja
Breña Baja is a coastal municipality on the eastern side of La Palma in Spain’s Canary Islands, known for its tourism, banana plantations, and proximity to the island’s main airport.
-
E.
Caleruega
Caleruega is a small town in the province of Burgos, Spain, best known as the birthplace of Saint Dominic, founder of the Dominican Order.
- 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: Beiras Triple: [Beira Litoral, historicalRegion, Beiras]
Generated description
Beiras is a traditional region in central Portugal known for its diverse landscapes, historic cities, and cultural heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Beiras Target entity description: Beiras is a traditional region in central Portugal known for its diverse landscapes, historic cities, and cultural heritage.
-
A.
Ribera
Ribera was a prominent 17th-century Spanish Baroque painter, known for his dramatic use of light and shadow and intense religious and genre scenes.
-
B.
Nalón
The Nalón is a major river in Asturias, northern Spain, known for flowing through mountainous landscapes and historically supporting regional industry and mining.
-
C.
Cosío
Cosío is a small municipality and town located in the northern part of the Mexican state of Aguascalientes.
-
D.
Breña Baja
Breña Baja is a coastal municipality on the eastern side of La Palma in Spain’s Canary Islands, known for its tourism, banana plantations, and proximity to the island’s main airport.
-
E.
Caleruega
Caleruega is a small town in the province of Burgos, Spain, best known as the birthplace of Saint Dominic, founder of the Dominican Order.
- 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_69ad85da0ba481908b3b48c69efe2b98 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc22a3cf081908c20b6fb55be0db2 |
completed | March 8, 2026, 6:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4330de7a08190933aa7e9dc0a65be |
completed | March 13, 2026, 3:53 p.m. |
| NEDg | Description generation | batch_69b437cf839881909b1d505328285123 |
completed | March 13, 2026, 4:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b43835994c81909230bbb21b12b8ef |
completed | March 13, 2026, 4:15 p.m. |
Created at: March 8, 2026, 3:22 p.m.