Triple
T13894621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MSN Messenger |
E334055
|
entity |
| Predicate | partOf |
P40
|
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: [MSN Messenger, partOf, MSN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MSN Context triple: [MSN Messenger, partOf, MSN]
-
A.
MSN
MSN is the National Rail station code for Marsden railway station in West Yorkshire, England.
-
B.
MSN
chosen
MSN is a Microsoft-owned web portal and collection of Internet services offering news, entertainment, email, and other online content.
-
C.
MSN
MSN is the three-letter IATA airport code for Dane County Regional Airport serving Madison, Wisconsin.
-
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 two-letter ISO 3166 country code assigned to the British Overseas Territory of Montserrat in the Caribbean.
- 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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a741908190bdf46d76c5f1411a |
completed | April 14, 2026, 11:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c71eb1808190b0a3a28a8011e9c7 |
completed | May 3, 2026, 10:07 p.m. |
Created at: April 9, 2026, 10:15 p.m.