Triple
T26780010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Crawford Hotel |
E670220
|
entity |
| Predicate | blendOf |
P158304
|
FINISHED |
| Object | historic architecture |
—
|
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: historic architecture | Statement: [The Crawford Hotel, blendOf, historic architecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: blendOf Context triple: [The Crawford Hotel, blendOf, historic architecture]
-
A.
hasBlendOf
chosen
Indicates that something is composed of or contains a mixture of multiple specified components or elements.
-
B.
isBlended
Indicates that one entity has been mixed or combined thoroughly with another (or others) to form a uniform whole.
-
C.
blendingRole
Indicates the specific function or contribution an entity has within a mixture or combination process.
-
D.
mixesWith
Indicates that one entity is combined or blended together with another entity to form a mixture.
-
E.
usedInBlends
Indicates that something serves as an ingredient or component within one or more mixtures, combinations, or blends.
- 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_69eeb31c925881909b597f6e40056d28 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f619795b208190b039e396ab4629b2 |
completed | May 2, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69f60b8dfa0c8190864e1a940024d0a0 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 27, 2026, 4:08 a.m.