Triple
T5760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of the United States |
E112
|
entity |
| Predicate | residenceType |
P542
|
FINISHED |
| Object | official residence |
—
|
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: official residence | Statement: [President of the United States, residenceType, official residence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: residenceType Context triple: [President of the United States, residenceType, official residence]
-
A.
residence
Indicates that one entity lives at, is based in, or habitually occupies the location represented by the other entity.
-
B.
typeOfInstitution
Indicates the specific kind or category of institution that an entity belongs to or is classified as.
-
C.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
-
D.
area
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
-
E.
locatedIn
Indicates that one entity exists or is situated within the spatial, administrative, or conceptual boundaries of another entity.
- 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_69a238d6b47881909e68288aed2fd858 |
completed | Feb. 28, 2026, 12:37 a.m. |
| NER | Named-entity recognition | batch_69a23ae754fc8190812506055ce94672 |
completed | Feb. 28, 2026, 12:46 a.m. |
| PD | Predicate disambiguation | batch_69a239997f888190bf941b74fbc9c15f |
completed | Feb. 28, 2026, 12:40 a.m. |
| PDg | Predicate description generation | batch_69a23ae6766c8190bb805cf0ab137a19 |
completed | Feb. 28, 2026, 12:46 a.m. |
Created at: Feb. 28, 2026, 12:40 a.m.