Triple
T19692332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BusinessWeek 25 Most Influential People on the Web (2007) |
E472864
|
entity |
| Predicate | publisher |
P29
|
FINISHED |
| Object | BusinessWeek |
—
|
NE NERFINISHED |
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: BusinessWeek | Statement: [BusinessWeek 25 Most Influential People on the Web (2007), publisher, BusinessWeek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BusinessWeek Context triple: [BusinessWeek 25 Most Influential People on the Web (2007), publisher, BusinessWeek]
-
A.
BusinessWeek
chosen
BusinessWeek is a major American business magazine known for its coverage of global markets, companies, and economic trends.
-
B.
Business Insider
Business Insider is a digital media company that focuses on business, financial, and technology news and analysis.
-
C.
WSJ
WSJ is the Indian Railways station code for Wansjaliya Junction railway station in Gujarat, India.
-
D.
The Wall Street Journal
The Wall Street Journal is a leading American business-focused daily newspaper known for its influential financial reporting and analysis.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e515bef88190bc30781aea50537a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e64210cddc8190836faa2996a44457 |
completed | April 20, 2026, 3:11 p.m. |
Created at: April 10, 2026, 1:46 p.m.