Triple
T38635266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Microsoft Excel 2003 |
E937558
|
entity |
| Predicate | maximumColumnsPerWorksheet |
P15257
|
FINISHED |
| Object | 256 |
—
|
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: 256 | Statement: [Microsoft Excel 2003, maximumColumnsPerWorksheet, 256]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumColumnsPerWorksheet Context triple: [Microsoft Excel 2003, maximumColumnsPerWorksheet, 256]
-
A.
maximumRowsPerWorksheet
Indicates the maximum number of rows that are allowed in a single worksheet.
-
B.
maxNumberOfValues
Indicates the maximum count of distinct values that may be associated with a given entity or property in this relationship.
-
C.
numberOfColumns
chosen
Indicates the total count of vertical divisions (columns) associated with or contained in a given structure or dataset.
-
D.
numberOfMajorColumns
Indicates the total count of major columns associated with or contained in a given entity.
-
E.
maximumNumberOfSegments
Indicates the greatest allowable or observed count of discrete segments into which something can be or is divided.
- 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_69f76ed5ca3c81909288f61fbf37b359 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fddac4e2f48190a9301d3422658b29 |
completed | May 8, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69fdda06969c8190b5d033964ea2a690 |
completed | May 8, 2026, 12:41 p.m. |
Created at: May 3, 2026, 4:32 p.m.