Triple
T36794975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bogotá street grid |
E909158
|
entity |
| Predicate | usesStreetType |
P165387
|
FINISHED |
| Object | calle |
—
|
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: calle | Statement: [Bogotá street grid, usesStreetType, calle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesStreetType Context triple: [Bogotá street grid, usesStreetType, calle]
-
A.
correspondsToStreetType
chosen
Indicates that one entity matches or is associated with a particular type or classification of street.
-
B.
cityStreetUsed
Indicates that a particular city street is utilized or traversed in the course of some activity, route, or event.
-
C.
streetSet
Indicates that a particular street belongs to, or is included within, a specified set or collection of streets.
-
D.
isNumberedStreet
Indicates that a street is designated primarily by a number (e.g., "1st Street," "42nd Avenue") rather than by a proper name.
-
E.
hasStreet
Indicates that an entity is located on, associated with, or identified by a particular street.
- 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_69f76e7b98888190899b6478a82ad6ae |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fdb45537288190b6791078d4a6899f |
completed | May 8, 2026, 10 a.m. |
| PD | Predicate disambiguation | batch_69fdb39ad96481908376d7def9fafc13 |
completed | May 8, 2026, 9:57 a.m. |
Created at: May 3, 2026, 4:12 p.m.