Triple
T12771676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linha da Beira Baixa |
E305260
|
entity |
| Predicate | connectsAreaToCountry |
P2564
|
FINISHED |
| Object | Beira Baixa to rest of Portugal |
—
|
LITERAL FINISHED |
How this triple was built (2 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: Beira Baixa to rest of Portugal | Statement: [Linha da Beira Baixa, connectsAreaToCountry, Beira Baixa to rest of Portugal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsAreaToCountry Context triple: [Linha da Beira Baixa, connectsAreaToCountry, Beira Baixa to rest of Portugal]
-
A.
connectsCountryOrRegion
Indicates that one entity establishes a connection, link, or association to a specific country or region.
-
B.
connectsArea
chosen
Indicates that one area serves as a link or passage between two other areas, enabling movement or interaction between them.
-
C.
connectsAdministrativeArea
Indicates a relationship where one entity serves as a link or route between two administrative areas (such as regions, districts, or municipalities).
-
D.
connectsCountryBorder
Indicates that one entity forms a direct land or maritime border connection with a specified country.
-
E.
connectsRegions
Indicates a relationship where one entity links or joins two or more distinct regions, enabling passage, interaction, or continuity between them.
- F. None of above.
Provenance (3 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df5b68481908a5d40516b09be52 |
completed | April 10, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69d96409739881909174ba005a986cb5 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:28 p.m.