Triple
T5501100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese Room (Smith Tower) |
E144329
|
entity |
| Predicate | hasInteriorDesignTheme |
P5509
|
FINISHED |
| Object | Chinese-inspired decor |
—
|
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: Chinese-inspired decor | Statement: [Chinese Room (Smith Tower), hasInteriorDesignTheme, Chinese-inspired decor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInteriorDesignTheme Context triple: [Chinese Room (Smith Tower), hasInteriorDesignTheme, Chinese-inspired decor]
-
A.
interiorStyle
chosen
Indicates that one entity has a particular interior design style or aesthetic characterized by the other entity.
-
B.
hasCentralTheme
Indicates that one entity serves as the primary or dominant theme or subject matter of another entity.
-
C.
hasInteriorFeature
Indicates that an entity contains or includes a specific feature within its interior space.
-
D.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
E.
hasThemeType
Indicates that something is associated with or characterized by a particular thematic category or type.
- 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_69c008f5a2748190bce7a39aabf87a6d |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f08c2a4819093e772a1497c7ecc |
completed | March 22, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69c01b052f3c81909f71c6add0f35a6f |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:32 p.m.