Triple
T4974096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One Canada Square |
E111722
|
entity |
| Predicate | rankInLondonByHeight |
P27607
|
FINISHED |
| Object | one of the tallest buildings in London |
—
|
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: one of the tallest buildings in London | Statement: [One Canada Square, rankInLondonByHeight, one of the tallest buildings in London]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankInLondonByHeight Context triple: [One Canada Square, rankInLondonByHeight, one of the tallest buildings in London]
-
A.
rankingInEnglandByHeight
Indicates the relative position of an entity in an ordered list based on its height specifically within the context of England.
-
B.
rankInCityByHeight
chosen
Indicates the relative ordering of entities within a specific city based on their height, such as which is tallest, second tallest, and so on.
-
C.
rankAmongTallestBuildings
Indicates that one building is among the tallest buildings within a specified group, area, or category.
-
D.
tallestBuildingIn
Indicates that one entity is the tallest building located within the area or region specified by the other entity.
-
E.
towerName
Indicates the specific name assigned to a tower in the relationship.
- 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_69bd441a0eb481908050fa4273b19eae |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd730a7590819088ab8d49c5c88c2f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd7146e6e881908a55ab2756b631f6 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:33 p.m.