Triple
T2782615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A. T. & T. Building, Kansas City, Missouri |
E61730
|
entity |
| Predicate | hasArchitectNationality |
P12560
|
FINISHED |
| Object | American |
—
|
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: American | Statement: [A. T. & T. Building, Kansas City, Missouri, hasArchitectNationality, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArchitectNationality Context triple: [A. T. & T. Building, Kansas City, Missouri, hasArchitectNationality, American]
-
A.
architectNationality
chosen
Indicates the country or national affiliation associated with an architect.
-
B.
designerNationality
Indicates that a designer has a specific national or country affiliation.
-
C.
namedForNationality
Indicates that something is named after or in reference to a particular nationality or national identity.
-
D.
associatedComposerNationality
Indicates that there is a relationship between a composer and a specific nationality with which that composer is identified or associated.
-
E.
hasDirectorNationality
Indicates that the nationality of a director is associated with a given entity (such as a film, organization, or work).
- 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_69ab4b7e43c48190997b8fc8fb1663ab |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddceb9d88190961e30d521a21552 |
completed | March 7, 2026, 8:11 a.m. |
| PD | Predicate disambiguation | batch_69abdd00b65c8190a8ea444308c4fa2b |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:57 p.m.