Triple
T8104931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ministry of Health building |
E189203
|
entity |
| Predicate | partOfSkyline |
P56210
|
FINISHED |
| Object | Buenos Aires city centre |
—
|
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: Buenos Aires city centre | Statement: [Ministry of Health building, partOfSkyline, Buenos Aires city centre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfSkyline Context triple: [Ministry of Health building, partOfSkyline, Buenos Aires city centre]
-
A.
partOfSkylineOf
chosen
Indicates that one entity is a visible component or feature contributing to the overall skyline profile of another entity, typically a city or urban area.
-
B.
isSkyscraperIn
Indicates that a skyscraper is located within or belongs to a specified geographic area or place.
-
C.
isPartOfStreetscape
Indicates that something forms a component or element within the overall layout or visual composition of a streetscape.
-
D.
locatedInSkyscraper
Indicates that one entity is physically situated within or inside a skyscraper.
-
E.
architectOfSurroundingBuildings
Indicates that one entity is the architect responsible for designing the buildings that surround or are adjacent to another specified 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_69ca82b9d5848190a24672775d5c5011 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb42c0ce6481909887be82c8019383 |
completed | March 31, 2026, 3:42 a.m. |
| PD | Predicate disambiguation | batch_69cb04a2ed1c8190b73562321ad688bc |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:31 p.m.