Triple
T3153078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buenos Aires Metropolitan Cathedral |
E65920
|
entity |
| Predicate | cityGateCoordinateType |
P1573
|
FINISHED |
| Object | city center of Buenos Aires |
—
|
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: city center of Buenos Aires | Statement: [Buenos Aires Metropolitan Cathedral, cityGateCoordinateType, city center of Buenos Aires]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityGateCoordinateType Context triple: [Buenos Aires Metropolitan Cathedral, cityGateCoordinateType, city center of Buenos Aires]
-
A.
cityGateAxisTerminus
Indicates the point or structure where a principal axis or thoroughfare of a city terminates at or aligns with a city gate.
-
B.
cityGateTo
Indicates a directional relationship where one location or path leads to or opens into a city gate.
-
C.
headquartersCoordinates
Indicates the geographic coordinates where an entity’s main headquarters is located.
-
D.
coordinateLocation
chosen
Indicates that an entity is located at, or associated with, a specific geographic coordinate or set of coordinates.
-
E.
cityGatesName
Indicates that a set of city gates bears or is identified by a specific name.
- 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_69ad8584485081909ed529e890cadc4a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada5c3d6d481908c296e9e09c07f6f |
completed | March 8, 2026, 4:37 p.m. |
| PD | Predicate disambiguation | batch_69ad9dfbf0348190952a6bca8fc5fed1 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:05 p.m.