Triple
T3698858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Évora District |
E78524
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Mourão
Mourão is a small municipality in Portugal’s Alentejo region, known for its historic castle and proximity to the Alqueva Reservoir.
|
E384237
|
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: Mourão | Statement: [Évora District, contains, Mourão]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mourão Context triple: [Évora District, contains, Mourão]
-
A.
Guaratinguetá
Guaratinguetá is a historic municipality in southeastern Brazil known for its colonial heritage and religious tourism, located in the state of São Paulo.
-
B.
Sertãozinho
Sertãozinho is a municipality in the interior of Brazil known for its strong sugarcane-based agribusiness and ethanol production.
-
C.
Morrinhos
Morrinhos is a municipality in the Brazilian state of Goiás, known for its agricultural economy and regional thermal springs.
-
D.
Taquaritinga
Taquaritinga is a municipality in the interior of Brazil’s São Paulo state, known for its agricultural production and regional commerce.
-
E.
Ribeirão Pires
Ribeirão Pires is a municipality in the Greater São Paulo metropolitan region of Brazil, known for its green areas and role as a residential and service hub near the state 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: Mourão Triple: [Évora District, contains, Mourão]
Generated description
Mourão is a small municipality in Portugal’s Alentejo region, known for its historic castle and proximity to the Alqueva Reservoir.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mourão Target entity description: Mourão is a small municipality in Portugal’s Alentejo region, known for its historic castle and proximity to the Alqueva Reservoir.
-
A.
Guaratinguetá
Guaratinguetá is a historic municipality in southeastern Brazil known for its colonial heritage and religious tourism, located in the state of São Paulo.
-
B.
Sertãozinho
Sertãozinho is a municipality in the interior of Brazil known for its strong sugarcane-based agribusiness and ethanol production.
-
C.
Morrinhos
Morrinhos is a municipality in the Brazilian state of Goiás, known for its agricultural economy and regional thermal springs.
-
D.
Taquaritinga
Taquaritinga is a municipality in the interior of Brazil’s São Paulo state, known for its agricultural production and regional commerce.
-
E.
Ribeirão Pires
Ribeirão Pires is a municipality in the Greater São Paulo metropolitan region of Brazil, known for its green areas and role as a residential and service hub near the state 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_69ad85e3b1888190abc983e06968696d |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc512ba188190a15bcacafac3f476 |
completed | March 8, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4db01e118819090438d80898cf73b |
completed | March 14, 2026, 3:50 a.m. |
| NEDg | Description generation | batch_69b4dbd0b6e88190a857afe3c1041788 |
completed | March 14, 2026, 3:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4dc5114ec8190aee92e21a48ae268 |
completed | March 14, 2026, 3:56 a.m. |
Created at: March 8, 2026, 3:26 p.m.