Triple
T5581991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Puerto Iguazú |
E146660
|
entity |
| Predicate | transportModeImportant |
P64592
|
FINISHED |
| Object | road transport |
—
|
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: road transport | Statement: [Puerto Iguazú, transportModeImportant, road transport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportModeImportant Context triple: [Puerto Iguazú, transportModeImportant, road transport]
-
A.
transportModeFamily
Indicates the general category or family of transportation mode to which a specific transport mode belongs (e.g., road, rail, air, water).
-
B.
transportType
Indicates the mode or means of transportation used in carrying something or someone from one place to another.
-
C.
transportModeAccess
Indicates that one entity has the ability or permission to use, reach, or be served by a particular mode of transportation.
-
D.
publicTransitMode
Indicates the type of public transportation (e.g., bus, train, subway) used or associated with a given trip or segment.
-
E.
transportModeIntegration
Indicates that different modes of transportation are coordinated or combined to enable seamless or efficient movement within a journey or transport system.
- F. None of above. chosen
Provenance (4 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_69c0090287a08190b4098411effe970c |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0208333f08190bf0049b6bdd280f5 |
completed | March 22, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69c01b147cc081909237f3f2967d4cb8 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f0684908190ae2d14f0bd2ab892 |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:37 p.m.