Triple
T8183373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minho region |
E191121
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object |
Esposende
Esposende is a coastal city and municipality in northern Portugal, known for its Atlantic beaches, natural parks, and traditional fishing heritage.
|
E716728
|
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: Esposende | Statement: [Minho region, hasMajorCity, Esposende]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Esposende Context triple: [Minho region, hasMajorCity, Esposende]
-
A.
Alvescot
Alvescot is a small rural village in Oxfordshire, England, known for its traditional stone cottages and historic parish church.
-
B.
Frasqueira
Frasqueira is a premium category of Madeira wine denoting long-aged, high-quality vintage bottlings.
-
C.
Arruda
Arruda is a neighborhood in Recife, Brazil, best known for housing the Estádio do Arruda, home stadium of the Santa Cruz Futebol Clube.
-
D.
Lacanha
Lacanha is an ancient Maya archaeological site in the western lowlands of Chiapas, Mexico, known for its ruins, inscriptions, and role within the Classic-period Maya civilization.
-
E.
Cacilhas
Cacilhas is a riverside district in Almada, Portugal, known for its ferry link to Lisbon and its waterfront restaurants and bars.
- 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: Esposende Triple: [Minho region, hasMajorCity, Esposende]
Generated description
Esposende is a coastal city and municipality in northern Portugal, known for its Atlantic beaches, natural parks, and traditional fishing heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Esposende Target entity description: Esposende is a coastal city and municipality in northern Portugal, known for its Atlantic beaches, natural parks, and traditional fishing heritage.
-
A.
Alvescot
Alvescot is a small rural village in Oxfordshire, England, known for its traditional stone cottages and historic parish church.
-
B.
Frasqueira
Frasqueira is a premium category of Madeira wine denoting long-aged, high-quality vintage bottlings.
-
C.
Arruda
Arruda is a neighborhood in Recife, Brazil, best known for housing the Estádio do Arruda, home stadium of the Santa Cruz Futebol Clube.
-
D.
Lacanha
Lacanha is an ancient Maya archaeological site in the western lowlands of Chiapas, Mexico, known for its ruins, inscriptions, and role within the Classic-period Maya civilization.
-
E.
Cacilhas
Cacilhas is a riverside district in Almada, Portugal, known for its ferry link to Lisbon and its waterfront restaurants and bars.
- 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_69ca82c4538081909404325aa5639483 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4c4f4ef88190ad346edad14b67ee |
completed | March 31, 2026, 4:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccbf8e8f0c819096f449760ce0d240 |
completed | April 1, 2026, 6:47 a.m. |
| NEDg | Description generation | batch_69ccc315132c8190bb0ad49232ccc3b8 |
completed | April 1, 2026, 7:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ccd87585148190a2d8b81ab352d123 |
completed | April 1, 2026, 8:33 a.m. |
Created at: March 30, 2026, 5:41 p.m.