Triple
T16854386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Microsoft Advertising |
E409748
|
entity |
| Predicate | integratesWith |
P1075
|
FINISHED |
| Object | MSN |
E438362
|
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: MSN | Statement: [Microsoft Advertising, integratesWith, MSN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MSN Context triple: [Microsoft Advertising, integratesWith, MSN]
-
A.
MSN
MSN is the three-letter IATA airport code for Dane County Regional Airport serving Madison, Wisconsin.
-
B.
MSN
MSN is the National Rail station code for Marsden railway station in West Yorkshire, England.
-
C.
MSN
chosen
MSN is a Microsoft-owned web portal and collection of Internet services offering news, entertainment, email, and other online content.
-
D.
MSN Messenger
MSN Messenger was a widely used instant messaging client developed by Microsoft that enabled real-time text, voice, and video communication over the internet.
-
E.
MS
MS is the official vehicle registration code for the Brazilian state of Mato Grosso do Sul, whose capital is Campo Grande.
- 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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b37c6e808190975b14b228253029 |
completed | April 18, 2026, 4:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00bb216fac81909d401c6b9911d1e0 |
completed | May 10, 2026, 5:06 p.m. |
Created at: April 10, 2026, 5:24 a.m.