Triple
T6625174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Country Life |
E149779
|
entity |
| Predicate | hasRegularColumn |
P13119
|
FINISHED |
| Object | architecture column |
—
|
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 column | Statement: [Country Life, hasRegularColumn, architecture column]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegularColumn Context triple: [Country Life, hasRegularColumn, architecture column]
-
A.
hasColumns
chosen
Indicates that one entity possesses or is characterized by a set of columns associated with it.
-
B.
hasColumnCountBack
Indicates that an entity (such as a table or layout) has a specified number of columns on its back side or rear-facing section.
-
C.
hasFrontColumns
Indicates that one entity possesses or features columns located at its front side.
-
D.
hasColumnOrder
Indicates that one column in a sequence is positioned before or after another column, specifying their relative ordering.
-
E.
hasRow
Indicates that one entity contains, includes, or is associated with a specific row within a structured arrangement such as a table, grid, or dataset.
- 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_69c687ee50048190aa151765bef16193 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6bdb88cc881908f35648c15a7dc85 |
completed | March 27, 2026, 5:26 p.m. |
| PD | Predicate disambiguation | batch_69c6ad007c1c8190af425f51011c7ad1 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:58 p.m.