Triple
T15028893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alcanena |
E378288
|
entity |
| Predicate | hasParish |
P35
|
FINISHED |
| Object |
Espinheiro
Espinheiro is a civil parish located within the municipality of Alcanena in central Portugal.
|
E1133963
|
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: Espinheiro | Statement: [Alcanena, hasParish, Espinheiro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Espinheiro Context triple: [Alcanena, hasParish, Espinheiro]
-
A.
Espinheiro
Espinheiro is a central neighborhood in Recife, Brazil, known for its residential areas, commerce, and urban amenities.
-
B.
Celorico de Basto
Celorico de Basto is a municipality in northern Portugal known for its scenic landscapes, vineyards, and historic heritage within the Minho region.
-
C.
Cacilhas
Cacilhas is a riverside district in Almada, Portugal, known for its ferry link to Lisbon and its waterfront restaurants and bars.
-
D.
Mosteiros
Mosteiros is a coastal municipality on the island of Fogo in Cape Verde, known for its volcanic landscapes, coffee production, and black-sand beaches.
-
E.
Mosteiros
Mosteiros is a coastal civil parish on the western tip of São Miguel Island in the Azores, known for its volcanic rock formations, natural swimming pools, and scenic Atlantic views.
- 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: Espinheiro Triple: [Alcanena, hasParish, Espinheiro]
Generated description
Espinheiro is a civil parish located within the municipality of Alcanena in central Portugal.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Espinheiro Target entity description: Espinheiro is a civil parish located within the municipality of Alcanena in central Portugal.
-
A.
Espinheiro
Espinheiro is a central neighborhood in Recife, Brazil, known for its residential areas, commerce, and urban amenities.
-
B.
Celorico de Basto
Celorico de Basto is a municipality in northern Portugal known for its scenic landscapes, vineyards, and historic heritage within the Minho region.
-
C.
Cacilhas
Cacilhas is a riverside district in Almada, Portugal, known for its ferry link to Lisbon and its waterfront restaurants and bars.
-
D.
Mosteiros
Mosteiros is a coastal municipality on the island of Fogo in Cape Verde, known for its volcanic landscapes, coffee production, and black-sand beaches.
-
E.
Mosteiros
Mosteiros is a coastal civil parish on the western tip of São Miguel Island in the Azores, known for its volcanic rock formations, natural swimming pools, and scenic Atlantic views.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7e0e8c88190ac6f5786b4d4040f |
completed | April 15, 2026, 12:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9dd967588190821cf47e9734db21 |
completed | May 9, 2026, 2:37 a.m. |
| NEDg | Description generation | batch_69fe9e5dbbe0819084567688758b0245 |
completed | May 9, 2026, 2:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe9eedca1481908ce438991184d62e |
completed | May 9, 2026, 2:41 a.m. |
Created at: April 10, 2026, 2:58 a.m.