Triple
T3701467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aon Center |
E78587
|
entity |
| Predicate | rankingInChicagoByHeight |
P27607
|
FINISHED |
| Object | third tallest building |
—
|
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: third tallest building | Statement: [Aon Center, rankingInChicagoByHeight, third tallest building]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankingInChicagoByHeight Context triple: [Aon Center, rankingInChicagoByHeight, third tallest building]
-
A.
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.
-
B.
tallestBuildingIn
Indicates that one entity is the tallest building located within the area or region specified by the other entity.
-
C.
rankAmongTallestBuildings
Indicates that one building is among the tallest buildings within a specified group, area, or category.
-
D.
rankInShanghaiByHeightCurrent
Indicates the position an entity currently holds in a ranking of heights within Shanghai, ordered from tallest to shortest.
-
E.
buildingHeight
Indicates the vertical extent or height measurement of a building.
- 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_69ad85e3b1888190abc983e06968696d |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc547c1848190a1ece46c59b7c43d |
completed | March 8, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69adb84eeca48190bb4de637e9f0e27a |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:26 p.m.