Triple
T570302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomson Reuters |
E13647
|
entity |
| Predicate | hasBusinessSegment |
P1670
|
FINISHED |
| Object | Reuters News |
E18673
|
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: Reuters News | Statement: [Thomson Reuters, hasBusinessSegment, Reuters News]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Reuters News Context triple: [Thomson Reuters, hasBusinessSegment, Reuters News]
-
A.
Reuters
chosen
Reuters is a major international news agency and media organization known for providing real-time news and financial information to outlets and markets worldwide.
-
B.
Associated Press
The Associated Press is a major American not-for-profit news agency and cooperative known for its global news coverage and influential photojournalism.
-
C.
Wikinews
Wikinews is a free, collaboratively written online news source that is part of the Wikimedia family of projects.
-
D.
Yahoo News
Yahoo News is a major online news and media platform providing global and local coverage across politics, business, entertainment, and more as part of the Yahoo digital ecosystem.
-
E.
CNN
CNN is a major American cable news television channel known for pioneering 24-hour news coverage and live reporting from global events.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b057e708190b4e5975516e58993 |
completed | March 1, 2026, 8:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5089de648819097efdaa016aa33d2 |
completed | March 2, 2026, 3:48 a.m. |
Created at: March 1, 2026, 7:33 p.m.