Triple
T27700281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avenida Entre Ríos at Hipólito Yrigoyen |
E698408
|
entity |
| Predicate | streetCrosses |
P47021
|
FINISHED |
| Object | Avenida Entre Ríos |
—
|
NE NERFINISHED |
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: Avenida Entre Ríos | Statement: [Avenida Entre Ríos at Hipólito Yrigoyen, streetCrosses, Avenida Entre Ríos]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: streetCrosses Context triple: [Avenida Entre Ríos at Hipólito Yrigoyen, streetCrosses, Avenida Entre Ríos]
-
A.
crossesStreet
Indicates that an entity moves from one side of a street to the other, traversing the street’s width.
-
B.
roadCrossingBetween
Indicates that a road crossing (such as a crosswalk or intersection crossing) exists between two locations or road segments, connecting them for passage across the road.
-
C.
crossedByHighway
Indicates that a highway passes across or through the extent of a given entity or area.
-
D.
mainRoadCrossingBetween
Indicates that a primary or main road intersects or passes between two specified locations or entities.
-
E.
crossingOf
chosen
Indicates that one entity serves as the intersection or crossing point of two or more linear features, such as roads, paths, or tracks.
- 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_69ef590ea74081908f0cd7500d85fa27 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f635a29ff08190bfd246ccaf0ddb4e |
completed | May 2, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f62c1a92648190835a2c5250d8c758 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 2:56 p.m.