Triple
T11654188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Microsoft Loop |
E276976
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | Loop pages |
E276974
|
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: Loop pages | Statement: [Microsoft Loop, hasComponent, Loop pages]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loop pages Context triple: [Microsoft Loop, hasComponent, Loop pages]
-
A.
Loop pages
chosen
Loop pages are flexible, collaborative workspaces within Microsoft Loop where users can organize and edit collections of Loop components, content, and tasks in real time.
-
B.
Stephanus pagination
Stephanus pagination is the standard scholarly system of page and section numbers used to reference and cite passages in the works of Plato.
-
C.
Pages
Pages is Apple's word processing and page layout application, part of the iWork productivity suite for macOS and iOS.
-
D.
Loop components
Loop components are portable, real-time collaborative content blocks in Microsoft 365 that can be shared and edited across apps like Teams, Outlook, and Word.
-
E.
Page
Page is a common English surname borne by numerous notable individuals across fields such as technology, entertainment, and politics.
- 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a3cee010819089cffdbefe5a6efb |
completed | April 10, 2026, 7:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef138faf4c81908043c71550048d75 |
completed | April 27, 2026, 7:43 a.m. |
Created at: April 8, 2026, 9:39 p.m.