Triple
T7563401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liberty Square |
E178847
|
entity |
| Predicate | hasRestroomDesignDetail |
P77041
|
FINISHED |
| Object | restrooms disguised due to colonial theming |
—
|
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: restrooms disguised due to colonial theming | Statement: [Liberty Square, hasRestroomDesignDetail, restrooms disguised due to colonial theming]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRestroomDesignDetail Context triple: [Liberty Square, hasRestroomDesignDetail, restrooms disguised due to colonial theming]
-
A.
hasRestrooms
Indicates that a place or facility provides access to restroom or toilet amenities.
-
B.
bathroomFeatures
chosen
Indicates that a bathroom includes or is equipped with specific features or amenities.
-
C.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
D.
designedArea
Indicates that an area has been intentionally planned, shaped, or configured according to a specific design or purpose.
-
E.
designedFacilityType
Indicates the type or category of facility that something (such as a plan, system, or component) is specifically designed for.
- 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_69c69f2f80288190b95cceb4da92ab2b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8fb1c00819096bdb73334d8d72e |
completed | March 27, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69c6f4dc485c819080da13e3b7f4f08f |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:50 p.m.