Triple
T3174785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Arrington |
E66435
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | TechCrunch blog |
E10979
|
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: TechCrunch blog | Statement: [Michael Arrington, notableWork, TechCrunch blog]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TechCrunch blog Context triple: [Michael Arrington, notableWork, TechCrunch blog]
-
A.
TechCrunch
chosen
TechCrunch is a leading technology news website and media platform known for its coverage of startups, Silicon Valley, and the tech industry.
-
B.
Engadget
Engadget is a technology news and reviews website that covers consumer electronics, gadgets, and digital culture.
-
C.
UBM Tech
UBM Tech was a business-to-business media and information company focused on the technology industry, known for publishing specialized tech publications and running industry events and conferences.
-
D.
Google I/O
Google I/O is Google’s annual developer conference focused on showcasing new technologies, software updates, and tools across its platforms and services.
-
E.
MIT Technology Review
MIT Technology Review is a technology-focused media outlet and magazine known for in-depth reporting and analysis on emerging technologies and their impact on society, business, and policy.
- 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_69ad8586a34c8190944c63ec11a8de1a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada670c800819098937783e2b05c7a |
completed | March 8, 2026, 4:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b28e4cdd2c8190a4b09e968b9d39be |
completed | March 12, 2026, 9:58 a.m. |
Created at: March 8, 2026, 3:06 p.m.