Triple
T1043138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | China Room |
E22512
|
entity |
| Predicate | hasDisplayedObject |
P5510
|
FINISHED |
| Object | state china of George Washington |
—
|
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: state china of George Washington | Statement: [China Room, hasDisplayedObject, state china of George Washington]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDisplayedObject Context triple: [China Room, hasDisplayedObject, state china of George Washington]
-
A.
hasObject
chosen
Indicates that an entity is associated with or possesses a particular object as part of a relationship or action.
-
B.
hasView
Indicates that one entity provides a visual perspective or outlook onto another entity or scene.
-
C.
hasDisplayType
Indicates the type or category of display associated with an entity, such as the format, mode, or presentation style used to show its content.
-
D.
hasSee
Indicates that one entity has perceived or visually observed another entity.
-
E.
displayedAt
Indicates that one entity is presented or exhibited at a particular location, venue, or event.
- 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_69a493d91478819094cc01fb65564bc1 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b845fa8c8190a7b69629883b62e2 |
completed | March 1, 2026, 10:05 p.m. |
| PD | Predicate disambiguation | batch_69a4b72ba60881908b017ef3b2b9645e |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.