Triple
T8881701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santiago do Cacém |
E211425
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
São Domingos
São Domingos is a civil parish within the municipality of Santiago do Cacém in Portugal, known for its rural character and traditional Alentejo landscape.
|
E765549
|
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: São Domingos | Statement: [Santiago do Cacém, hasPart, São Domingos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: São Domingos Context triple: [Santiago do Cacém, hasPart, São Domingos]
-
A.
São Domingos
São Domingos is a municipality on the island of Santiago in Cape Verde, known for its rural landscapes and traditional Cape Verdean culture.
-
B.
São Domingos de Ana Loura
São Domingos de Ana Loura is a small civil parish in the municipality of Estremoz, in Portugal’s Alentejo region.
-
C.
São Bartolomeu da Serra
São Bartolomeu da Serra is a small civil parish in the municipality of Santiago do Cacém in the Alentejo region of southern Portugal.
-
D.
Santa Cruz das Flores
Santa Cruz das Flores is the main town and administrative center of Flores Island in Portugal’s Azores archipelago.
-
E.
São Bento
São Bento is a civil parish within the municipality of Angra do Heroísmo on Terceira Island in Portugal’s Azores archipelago.
- 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: São Domingos Triple: [Santiago do Cacém, hasPart, São Domingos]
Generated description
São Domingos is a civil parish within the municipality of Santiago do Cacém in Portugal, known for its rural character and traditional Alentejo landscape.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: São Domingos Target entity description: São Domingos is a civil parish within the municipality of Santiago do Cacém in Portugal, known for its rural character and traditional Alentejo landscape.
-
A.
São Domingos
São Domingos is a municipality on the island of Santiago in Cape Verde, known for its rural landscapes and traditional Cape Verdean culture.
-
B.
São Domingos de Ana Loura
São Domingos de Ana Loura is a small civil parish in the municipality of Estremoz, in Portugal’s Alentejo region.
-
C.
São Bartolomeu da Serra
São Bartolomeu da Serra is a small civil parish in the municipality of Santiago do Cacém in the Alentejo region of southern Portugal.
-
D.
Santa Cruz das Flores
Santa Cruz das Flores is the main town and administrative center of Flores Island in Portugal’s Azores archipelago.
-
E.
São Bento
São Bento is a civil parish within the municipality of Angra do Heroísmo on Terceira Island in Portugal’s Azores archipelago.
- 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_69ca838f9e20819096ab1f236a70381a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6168e3d881908c58cf11cf5f9a0e |
completed | April 1, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfba1809dc81909776f1268cae9004 |
completed | April 3, 2026, 1:01 p.m. |
| NEDg | Description generation | batch_69cfbacea9408190a38f14817437c382 |
completed | April 3, 2026, 1:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfbb6235148190850865a734d55a6c |
completed | April 3, 2026, 1:06 p.m. |
Created at: March 30, 2026, 6:53 p.m.