Triple
T558943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Time Europe |
E13404
|
entity |
| Predicate | website |
P69
|
FINISHED |
| Object | https://time.com |
E801
|
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: https://time.com | Statement: [Time Europe, website, https://time.com]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: https://time.com Context triple: [Time Europe, website, https://time.com]
-
A.
CNN
CNN is a major American cable news television channel known for pioneering 24-hour news coverage and live reporting from global events.
-
B.
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.
-
C.
The New York Times
The New York Times is a leading American newspaper renowned for its influential journalism, extensive global coverage, and role as a newspaper of record.
-
D.
Wikinews
Wikinews is a free, collaboratively written online news source that is part of the Wikimedia family of projects.
-
E.
Time magazine
chosen
Time magazine is a long-running American weekly news magazine known for its influential coverage of global events, politics, and culture.
- 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_69a4933edcf08190b35ecfd6014caee6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a499df43f08190b514a38d36fc271d |
completed | March 1, 2026, 7:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4e9bb3b28819099ed0027d948483a |
completed | March 2, 2026, 1:36 a.m. |
Created at: March 1, 2026, 7:32 p.m.