Triple
T7632045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Group of a Thousand Columns |
E172779
|
entity |
| Predicate | hasApproximateNumberOfColumns |
P77444
|
FINISHED |
| Object | hundreds of columns |
—
|
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: hundreds of columns | Statement: [Group of a Thousand Columns, hasApproximateNumberOfColumns, hundreds of columns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfColumns Context triple: [Group of a Thousand Columns, hasApproximateNumberOfColumns, hundreds of columns]
-
A.
numberOfColumns
Indicates the total count of vertical divisions (columns) associated with or contained in a given structure or dataset.
-
B.
hasApproximateBrickCount
Indicates that an entity is associated with an estimated or non-exact number of bricks.
-
C.
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.
-
D.
hasApproximateMemberCount
Indicates that an entity is associated with a group or collection for which only an estimated or non-exact number of members is known.
-
E.
hasApproximateExtent
Indicates that one entity has a spatial, temporal, or quantitative extent that is only roughly or approximately specified rather than exact.
- 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_69c69952849881908fdcea7a93bfc307 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6faa4d2808190942129110711788b |
completed | March 27, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e8cadc8190b7977fcd213954dd |
completed | March 27, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69c6f574d8a8819095749518dad13791 |
completed | March 27, 2026, 9:24 p.m. |
Created at: March 27, 2026, 3:57 p.m.