Triple
T82113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Microsoft |
E1649
|
entity |
| Predicate | product |
P490
|
FINISHED |
| Object | Microsoft Office |
E1649
|
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: Microsoft Office | Statement: [Microsoft, product, Microsoft Office]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Microsoft Office Context triple: [Microsoft, product, Microsoft Office]
-
A.
Microsoft
chosen
Microsoft is a multinational technology company best known for its Windows operating system, Office productivity suite, and Azure cloud computing platform.
-
B.
ERP
ERP is the commonly used abbreviation for the Marshall Plan, the U.S.-led post–World War II European Recovery Program that financed and coordinated Western Europe’s economic reconstruction.
-
C.
Google
Google is a multinational technology company best known for its search engine and wide range of internet-related products and services, including Android, YouTube, and cloud computing.
-
D.
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.
-
E.
IBM
IBM is a multinational technology and consulting company known for its pioneering work in computer hardware, software, and enterprise services.
- 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a24f367b208190a69f5b76d6ae0496 |
completed | Feb. 28, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2555394f881909f01ec05c75ff63d |
completed | Feb. 28, 2026, 2:39 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.