Triple
T30580223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Architectural Record |
E778362
|
entity |
| Predicate | isWidelyReadBy |
P169872
|
FINISHED |
| Object | architecture professionals |
—
|
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: architecture professionals | Statement: [Architectural Record, isWidelyReadBy, architecture professionals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isWidelyReadBy Context triple: [Architectural Record, isWidelyReadBy, architecture professionals]
-
A.
isWidelyKnown
Indicates that something is generally recognized or familiar to a large number of people.
-
B.
isWidelyCoveredIn
Indicates that something receives extensive attention or reporting across many media outlets, sources, or platforms.
-
C.
isWidelyCoveredBy
Indicates that something receives extensive attention or reporting from many media outlets or information sources.
-
D.
isPopularAs
Indicates that an entity is widely liked, well-known, or favored in a particular role, context, or capacity.
-
E.
popularizedIn
Indicates that something became widely known, accepted, or fashionable within a particular place, time period, or context.
- F. None of above. chosen
Provenance (4 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_69f224a04b248190b0ca443ec86207b8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6894176d0819096fe66b9baab66f1 |
completed | May 2, 2026, 11:31 p.m. |
| PD | Predicate disambiguation | batch_69f67e42d6688190b60e91d2c388c555 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f6827a7b9c8190ab13605aacc81df9 |
completed | May 2, 2026, 11:02 p.m. |
Created at: April 29, 2026, 8:23 p.m.