Triple
T611196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coimbra |
E12101
|
entity |
| Predicate | demonym |
P191
|
FINISHED |
| Object |
Coimbrão
Coimbrão is the Portuguese term for a person from the city of Coimbra in central Portugal.
|
E12101
|
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: Coimbrão | Statement: [Coimbra, demonym, Coimbrão]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Coimbrão Context triple: [Coimbra, demonym, Coimbrão]
-
A.
Sabrosa
Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
-
B.
Vila Real de Santo António
Vila Real de Santo António is a coastal town and municipality in Portugal’s Algarve region, located at the mouth of the Guadiana River on the border with Spain.
-
C.
Coimbra
Coimbra is a historic Portuguese city known for its medieval architecture and the University of Coimbra, one of the oldest universities in continuous operation in the world.
-
D.
Silves
Silves is a historic town in southern Portugal known for its well-preserved Moorish castle and former status as the medieval capital of the Algarve region.
-
E.
Santervás de Campos
Santervás de Campos is a small municipality in the province of Valladolid, Spain, best known as the birthplace of the explorer Juan Ponce de León.
- 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: Coimbrão Triple: [Coimbra, demonym, Coimbrão]
Generated description
Coimbrão is the Portuguese term for a person from the city of Coimbra in central Portugal.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Coimbrão Target entity description: Coimbrão is the Portuguese term for a person from the city of Coimbra in central Portugal.
-
A.
Sabrosa
Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
-
B.
Vila Real de Santo António
Vila Real de Santo António is a coastal town and municipality in Portugal’s Algarve region, located at the mouth of the Guadiana River on the border with Spain.
-
C.
Coimbra
chosen
Coimbra is a historic Portuguese city known for its medieval architecture and the University of Coimbra, one of the oldest universities in continuous operation in the world.
-
D.
Silves
Silves is a historic town in southern Portugal known for its well-preserved Moorish castle and former status as the medieval capital of the Algarve region.
-
E.
Santervás de Campos
Santervás de Campos is a small municipality in the province of Valladolid, Spain, best known as the birthplace of the explorer Juan Ponce de León.
- F. None of above.
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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49df7c088819082eb70de4f0f4fbf |
completed | March 1, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a55a7561dc81908e2e2516c63c18a7 |
completed | March 2, 2026, 9:37 a.m. |
| NEDg | Description generation | batch_69a55b2152ac8190b034523d3a01f835 |
completed | March 2, 2026, 9:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a55b77d6448190acb5adc7a37aacd7 |
completed | March 2, 2026, 9:42 a.m. |
Created at: March 1, 2026, 7:35 p.m.