Triple
T15068563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porto de Mós |
E379816
|
entity |
| Predicate | hasCivilParish |
P2739
|
FINISHED |
| Object |
Mira de Aire
Mira de Aire is a civil parish in central Portugal known for its impressive limestone caves and natural park surroundings.
|
E1135550
|
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: Mira de Aire | Statement: [Porto de Mós, hasCivilParish, Mira de Aire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mira de Aire Context triple: [Porto de Mós, hasCivilParish, Mira de Aire]
-
A.
Mirada
Mirada is a film and television production company known for its creative storytelling and visual-driven projects.
-
B.
Del Aire
Del Aire is a small unincorporated community in Los Angeles County, California, known for its residential neighborhoods near Los Angeles International Airport.
-
C.
Milagro
Milagro is a city in Ecuador known as an important agricultural and commercial center, particularly for sugarcane and rice production.
-
D.
Cuatro Vientos
Cuatro Vientos is a station on Madrid’s C-5 commuter rail line, serving the Cuatro Vientos area in the southwest of the city.
-
E.
La Estrella
La Estrella is a municipality in the Antioquia department of Colombia, located in the metropolitan area of Medellín within the Aburrá Valley.
- 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: Mira de Aire Triple: [Porto de Mós, hasCivilParish, Mira de Aire]
Generated description
Mira de Aire is a civil parish in central Portugal known for its impressive limestone caves and natural park surroundings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mira de Aire Target entity description: Mira de Aire is a civil parish in central Portugal known for its impressive limestone caves and natural park surroundings.
-
A.
Mirada
Mirada is a film and television production company known for its creative storytelling and visual-driven projects.
-
B.
Del Aire
Del Aire is a small unincorporated community in Los Angeles County, California, known for its residential neighborhoods near Los Angeles International Airport.
-
C.
Milagro
Milagro is a city in Ecuador known as an important agricultural and commercial center, particularly for sugarcane and rice production.
-
D.
Cuatro Vientos
Cuatro Vientos is a station on Madrid’s C-5 commuter rail line, serving the Cuatro Vientos area in the southwest of the city.
-
E.
La Estrella
La Estrella is a municipality in the Antioquia department of Colombia, located in the metropolitan area of Medellín within the Aburrá Valley.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dedeebc7e48190a86b4f0afe8844bb |
completed | April 15, 2026, 12:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fea5cd4b6c8190aa9ff73d5be31864 |
completed | May 9, 2026, 3:11 a.m. |
| NEDg | Description generation | batch_69fea8e838b4819091e0a3d099c49059 |
completed | May 9, 2026, 3:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fea986e0dc8190a56e71288c6a7ef4 |
completed | May 9, 2026, 3:27 a.m. |
Created at: April 10, 2026, 3:02 a.m.