Triple
T14609566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barreiro da Faneca |
E342920
|
entity |
| Predicate | hasNameInPortuguese |
P1435
|
FINISHED |
| Object |
Barreiro da Faneca
Barreiro da Faneca is a locality in Portugal, likely a small settlement or geographic area whose name refers to a characteristic landscape or historical feature.
|
E1108150
|
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: Barreiro da Faneca | Statement: [Barreiro da Faneca, hasNameInPortuguese, Barreiro da Faneca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barreiro da Faneca Context triple: [Barreiro da Faneca, hasNameInPortuguese, Barreiro da Faneca]
-
A.
Póvoa de Lanhoso
Póvoa de Lanhoso is a municipality in northern Portugal known for its historic castle, traditional granite architecture, and scenic setting within the Minho region.
-
B.
Pedrógão
Pedrógão is a civil parish located within the municipality of Vidigueira in Portugal’s Alentejo region.
-
C.
Dão-Lafões
Dão-Lafões is a subregion in central Portugal known for its mountainous landscapes, thermal spas, and production of Dão wines.
-
D.
Barreiro
Barreiro is a small village located on the Cape Verdean island of Maio.
-
E.
Barreiro
Barreiro is a Portuguese city located on the south bank of the Tagus River opposite Lisbon, known historically for its industrial activity and as a commuter hub for the capital.
- 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: Barreiro da Faneca Triple: [Barreiro da Faneca, hasNameInPortuguese, Barreiro da Faneca]
Generated description
Barreiro da Faneca is a locality in Portugal, likely a small settlement or geographic area whose name refers to a characteristic landscape or historical feature.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Barreiro da Faneca Target entity description: Barreiro da Faneca is a locality in Portugal, likely a small settlement or geographic area whose name refers to a characteristic landscape or historical feature.
-
A.
Póvoa de Lanhoso
Póvoa de Lanhoso is a municipality in northern Portugal known for its historic castle, traditional granite architecture, and scenic setting within the Minho region.
-
B.
Pedrógão
Pedrógão is a civil parish located within the municipality of Vidigueira in Portugal’s Alentejo region.
-
C.
Dão-Lafões
Dão-Lafões is a subregion in central Portugal known for its mountainous landscapes, thermal spas, and production of Dão wines.
-
D.
Barreiro
Barreiro is a small village located on the Cape Verdean island of Maio.
-
E.
Barreiro
Barreiro is a Portuguese city located on the south bank of the Tagus River opposite Lisbon, known historically for its industrial activity and as a commuter hub for the capital.
- 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb44f0dd48190a78662b5998a6722 |
completed | April 14, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd94d22170819098df75754f5c12ab |
completed | May 8, 2026, 7:46 a.m. |
| NEDg | Description generation | batch_69fd975c51088190ac70093a591b9723 |
completed | May 8, 2026, 7:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd97f447488190958e79d776e2ed47 |
completed | May 8, 2026, 7:59 a.m. |
Created at: April 10, 2026, 1:25 a.m.