Triple
T22456809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Iberian |
E555137
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Barranquenho
Barranquenho is a mixed Portuguese–Spanish dialect spoken in the border region around Barrancos in southeastern Portugal.
|
E1537995
|
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: Barranquenho | Statement: [West Iberian, hasPart, Barranquenho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barranquenho Context triple: [West Iberian, hasPart, Barranquenho]
-
A.
Requena
Requena is a historic inland town in Spain’s Valencian Community, known for its wine production and well-preserved medieval quarter.
-
B.
Requena
Requena is a small Peruvian city in the Loreto region, known as a remote Amazonian river port and gateway to surrounding rainforest communities.
-
C.
Cañete
Cañete is a coastal province and agricultural hub in central Peru, known for its fertile valleys, Afro-Peruvian cultural heritage, and production of crops like grapes and cotton.
-
D.
Cañete
Cañete is a historic town in the province of Cuenca, Spain, known for its medieval architecture and hilltop castle.
-
E.
Cañete
Cañete is a Chilean city and commune in the Biobío Region, historically significant as a colonial frontier town in the Arauco War.
- 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: Barranquenho Triple: [West Iberian, hasPart, Barranquenho]
Generated description
Barranquenho is a mixed Portuguese–Spanish dialect spoken in the border region around Barrancos in southeastern Portugal.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Barranquenho Target entity description: Barranquenho is a mixed Portuguese–Spanish dialect spoken in the border region around Barrancos in southeastern Portugal.
-
A.
Requena
Requena is a small Peruvian city in the Loreto region, known as a remote Amazonian river port and gateway to surrounding rainforest communities.
-
B.
Requena
Requena is a historic inland town in Spain’s Valencian Community, known for its wine production and well-preserved medieval quarter.
-
C.
Cañete
Cañete is a coastal province and agricultural hub in central Peru, known for its fertile valleys, Afro-Peruvian cultural heritage, and production of crops like grapes and cotton.
-
D.
Cañete
Cañete is a historic town in the province of Cuenca, Spain, known for its medieval architecture and hilltop castle.
-
E.
Cañete
Cañete is a Chilean city and commune in the Biobío Region, historically significant as a colonial frontier town in the Arauco War.
- 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_69e11e51fdec8190adfdf9f8a6362221 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b7c428c8190847a259eef969525 |
completed | April 29, 2026, 1:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b0c7fc40081909f27eb081ac156f1 |
completed | May 18, 2026, 12:56 p.m. |
| NEDg | Description generation | batch_6a0b0ddb116c8190b19f9a01abb737e6 |
completed | May 18, 2026, 1:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b0e4402e481909210c5feff3fcddf |
completed | May 18, 2026, 1:04 p.m. |
Created at: April 16, 2026, 8:48 p.m.