Triple
T7464302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chase Tower (Dallas) |
E176333
|
entity |
| Predicate | rankInDallasByHeight |
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: [Chase Tower (Dallas), rankInDallasByHeight, one of the tallest buildings in Dallas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankInDallasByHeight Context triple: [Chase Tower (Dallas), rankInDallasByHeight, one of the tallest buildings in Dallas]
-
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.
rankAmongTallestBuildings
Indicates that one building is among the tallest buildings within a specified group, area, or category.
-
C.
averageHeight
Indicates that the relationship specifies the mean height value calculated from a set of entities or measurements.
-
D.
rankInShanghaiByHeightCurrent
Indicates the position an entity currently holds in a ranking of heights within Shanghai, ordered from tallest to shortest.
-
E.
populationRankInTexas
Indicates the relative position of an entity in terms of population size compared to other entities within Texas.
- 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_69c69f21632481908bf83f6c6da897e3 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f3d9d25c819087efc772b5b127fa |
completed | March 27, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69c6f03bad9c8190bdd5abb86d37df47 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:40 p.m.