Triple
T264791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Microsoft Teams |
E5699
|
entity |
| Predicate | integratesWith |
P1075
|
FINISHED |
| Object | Excel |
E5278
|
NE 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: Excel | Statement: [Microsoft Teams, integratesWith, Excel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Excel Context triple: [Microsoft Teams, integratesWith, Excel]
-
A.
Excel
chosen
Excel is a widely used spreadsheet software by Microsoft that enables data organization, analysis, visualization, and basic to advanced analytics through formulas, functions, and tools like PivotTables.
-
B.
Lotus 1-2-3
Lotus 1-2-3 is a pioneering spreadsheet software program for personal computers that became a dominant business application in the 1980s.
-
C.
Tableau
Tableau is a widely used data visualization and business intelligence software platform that enables users to analyze, explore, and present data through interactive dashboards and reports.
-
D.
Power BI
Power BI is a Microsoft business analytics and data visualization platform used to transform, analyze, and present data through interactive dashboards and reports.
-
E.
Microsoft 365
Microsoft 365 is a subscription-based suite of productivity and collaboration tools that combines Office applications with cloud services, security features, and device management.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a2587daeb081909591b9d30f80a271 |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25d8f9bbc8190a13841e4de093a66 |
completed | Feb. 28, 2026, 3:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a389ae45648190966804664bf4f861 |
completed | March 1, 2026, 12:34 a.m. |
Created at: Feb. 28, 2026, 2:56 a.m.