Triple
T1402932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bank of America Plaza (Dallas) |
E31625
|
entity |
| Predicate | rankInCityByHeight |
P27607
|
FINISHED |
| Object | one of the tallest buildings in Dallas |
—
|
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 Dallas | Statement: [Bank of America Plaza (Dallas), rankInCityByHeight, one of the tallest buildings in Dallas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankInCityByHeight Context triple: [Bank of America Plaza (Dallas), rankInCityByHeight, one of the tallest buildings in Dallas]
-
A.
rankInShanghaiByHeightCurrent
Indicates the position an entity currently holds in a ranking of heights within Shanghai, ordered from tallest to shortest.
-
B.
tallestBuildingIn
Indicates that one entity is the tallest building located within the area or region specified by the other entity.
-
C.
towerName
Indicates the specific name assigned to a tower in the relationship.
-
D.
rankByHeightWorld
Indicates an ordering of entities based on their relative height compared to all others in the world.
-
E.
rankInShanghaiByHeightAtCompletion
Indicates the numerical position an entity holds in a Shanghai-wide ranking ordered by its height at the time it was completed.
- F. None of above. chosen
Provenance (4 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_69a49918e1f88190ba610f9dc8114578 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c39ef554819096c17bca5891829b |
completed | March 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69a4bf030a388190bc82d30b9233e873 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c11067b48190bca6ef3ac1475c20 |
completed | March 1, 2026, 10:43 p.m. |
Created at: March 1, 2026, 7:59 p.m.