Triple
T16193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White House |
E323
|
entity |
| Predicate | occupant |
P75
|
FINISHED |
| Object | president of the United States |
—
|
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: president of the United States | Statement: [White House, occupant, president of the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupant Context triple: [White House, occupant, president of the United States]
-
A.
residence
chosen
Indicates that one entity lives at, is based in, or habitually occupies the location represented by the other entity.
-
B.
ownedBy
Indicates that one entity possesses legal or rightful ownership of another entity.
-
C.
residenceType
Indicates the kind or category of dwelling or living arrangement associated with an entity.
-
D.
spouse
Indicates that two entities are married to each other in a legally or socially recognized partnership.
-
E.
presentedBy
Indicates that something (such as an event, performance, or work) is formally organized, hosted, or introduced by a particular person or entity.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a241ea1ea081908e8a81ca97531ba5 |
completed | Feb. 28, 2026, 1:16 a.m. |
| PD | Predicate disambiguation | batch_69a23fec1fe8819080da6f2c745dc8fd |
completed | Feb. 28, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.