Triple
T14316730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reuters Limited |
E354974
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Reuters Financial |
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 Financial | Statement: [Reuters Limited, hasPart, Reuters Financial]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Reuters Financial Context triple: [Reuters Limited, hasPart, Reuters Financial]
-
A.
Bloomberg News
Bloomberg News is a global financial and business news organization known for its real-time market coverage, data-driven reporting, and multimedia journalism.
-
B.
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.
-
C.
The Wall Street Journal
The Wall Street Journal is a leading American business-focused daily newspaper known for its influential financial reporting and analysis.
-
D.
Financial Times
The Financial Times is a leading international daily newspaper based in London, renowned for its global business, economic, and financial news coverage.
-
E.
Bloomberg
Bloomberg is a global financial, software, data, and media company best known for its real-time financial information terminals and business news 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_69d8278ed42c8190b9f882dcce611347 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8838e45c819080ee69dd39e3bd43 |
completed | April 14, 2026, 6:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd468a3b788190812ff0eed84fd139 |
completed | May 8, 2026, 2:12 a.m. |
Created at: April 10, 2026, 1:12 a.m.