Triple
T22119815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loures |
E546634
|
entity |
| Predicate | hasRuralArea |
P14399
|
FINISHED |
| Object |
Bucelas
Bucelas is a rural civil parish in the municipality of Loures, Portugal, known for its wine production and traditional countryside landscape.
|
E1519542
|
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: Bucelas | Statement: [Loures, hasRuralArea, Bucelas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bucelas Context triple: [Loures, hasRuralArea, Bucelas]
-
A.
Baarìa
Baarìa is an Italian epic drama film directed by Giuseppe Tornatore that chronicles several generations of life, politics, and love in a Sicilian town.
-
B.
Peredo
Peredo is a Spanish-language surname borne by various individuals, including figures in Latin American history and culture.
-
C.
Lahinja
Lahinja is a river in southeastern Slovenia known for flowing through the Bela Krajina region and forming part of the Lahinja Landscape Park.
-
D.
Provadia
Provadia is a historic town in northeastern Bulgaria known for its ancient salt production and nearby prehistoric settlement, considered one of Europe's earliest urban centers.
-
E.
Borriana
Borriana is a coastal town and municipality in eastern Spain known for its citrus agriculture and Mediterranean beaches.
- 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: Bucelas Triple: [Loures, hasRuralArea, Bucelas]
Generated description
Bucelas is a rural civil parish in the municipality of Loures, Portugal, known for its wine production and traditional countryside landscape.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bucelas Target entity description: Bucelas is a rural civil parish in the municipality of Loures, Portugal, known for its wine production and traditional countryside landscape.
-
A.
Baarìa
Baarìa is an Italian epic drama film directed by Giuseppe Tornatore that chronicles several generations of life, politics, and love in a Sicilian town.
-
B.
Peredo
Peredo is a Spanish-language surname borne by various individuals, including figures in Latin American history and culture.
-
C.
Lahinja
Lahinja is a river in southeastern Slovenia known for flowing through the Bela Krajina region and forming part of the Lahinja Landscape Park.
-
D.
Provadia
Provadia is a historic town in northeastern Bulgaria known for its ancient salt production and nearby prehistoric settlement, considered one of Europe's earliest urban centers.
-
E.
Borriana
Borriana is a coastal town and municipality in eastern Spain known for its citrus agriculture and Mediterranean beaches.
- 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_69e11e38b3848190ac3a4fa97d56e65a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12950f5348190b204fbc347fd5dab |
completed | April 28, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a8f1d3ba081909e9ba0fd165449a5 |
completed | May 18, 2026, 4:01 a.m. |
| NEDg | Description generation | batch_6a0a910348ac81909a2b3f5662971e2e |
completed | May 18, 2026, 4:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a91867738819092e49aa8a74cc20b |
completed | May 18, 2026, 4:11 a.m. |
Created at: April 16, 2026, 8:31 p.m.