Triple
T14070483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisbon–Porto main line |
E338592
|
entity |
| Predicate | connectsCapitalToMajorCity |
P12955
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Lisbon–Porto main line, connectsCapitalToMajorCity, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsCapitalToMajorCity Context triple: [Lisbon–Porto main line, connectsCapitalToMajorCity, yes]
-
A.
connectsMajorCity
Indicates that one entity serves as a link or route providing direct connection to a major city.
-
B.
connectsLargestCitiesOf
Indicates a relationship where something (typically a route, network, or infrastructure) links together the largest cities within a specified region or set.
-
C.
connectsMajorCityState
Indicates that something serves as a link or route between a major city and the state it belongs to.
-
D.
linkedToCapitalCity
chosen
Indicates a relationship where an entity is associated or connected to a capital city, typically as its relevant or corresponding urban center.
-
E.
capitalOrMajorCenter
Indicates that a location serves as a capital city or a primary major center (political, economic, or cultural hub) for a larger region or entity.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de568d0404819087e0fe37c72162cb |
completed | April 14, 2026, 3 p.m. |
| PD | Predicate disambiguation | batch_69de05adef888190b023ab42ef5076b6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:21 p.m.