Triple
T4691380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisbon public transport network |
E104040
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object |
Barreiro
Barreiro is a Portuguese city located on the south bank of the Tagus River opposite Lisbon, known historically for its industrial activity and as a commuter hub for the capital.
|
E527128
|
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: Barreiro | Statement: [Lisbon public transport network, connectsTo, Barreiro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barreiro Context triple: [Lisbon public transport network, connectsTo, Barreiro]
-
A.
Barreiro
Barreiro is a small village located on the Cape Verdean island of Maio.
-
B.
Sernancelhe
Sernancelhe is a municipality in northern Portugal known for its historic granite architecture, religious heritage, and scenic rural landscapes.
-
C.
Oeiras
Oeiras is a coastal municipality in the Lisbon metropolitan area of Portugal, known for its residential suburbs, business parks, and proximity to the capital.
-
D.
Covilhã
Covilhã is a city in central Portugal, historically known for its textile industry and as a gateway to the Serra da Estrela mountain range.
-
E.
Seixas
Seixas is a surname most notably associated with individuals of Portuguese and Sephardic Jewish heritage.
- 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: Barreiro Triple: [Lisbon public transport network, connectsTo, Barreiro]
Generated description
Barreiro is a Portuguese city located on the south bank of the Tagus River opposite Lisbon, known historically for its industrial activity and as a commuter hub for the capital.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Barreiro Target entity description: Barreiro is a Portuguese city located on the south bank of the Tagus River opposite Lisbon, known historically for its industrial activity and as a commuter hub for the capital.
-
A.
Barreiro
Barreiro is a small village located on the Cape Verdean island of Maio.
-
B.
Sernancelhe
Sernancelhe is a municipality in northern Portugal known for its historic granite architecture, religious heritage, and scenic rural landscapes.
-
C.
Oeiras
Oeiras is a coastal municipality in the Lisbon metropolitan area of Portugal, known for its residential suburbs, business parks, and proximity to the capital.
-
D.
Covilhã
Covilhã is a city in central Portugal, historically known for its textile industry and as a gateway to the Serra da Estrela mountain range.
-
E.
Seixas
Seixas is a surname most notably associated with individuals of Portuguese and Sephardic Jewish heritage.
- 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_69bd43df91f481908e9add1b617b60ef |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd639c94608190808e535d0abd08a0 |
completed | March 20, 2026, 3:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bfd70b4a7c8190852503f31142562e |
completed | March 22, 2026, 11:48 a.m. |
| NEDg | Description generation | batch_69bfd78bf35881908d304accaec98c9b |
completed | March 22, 2026, 11:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bfd7dc86488190b73dd2aa18d205b3 |
completed | March 22, 2026, 11:51 a.m. |
Created at: March 20, 2026, 1:16 p.m.