Triple
T1041671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oath Inc. |
E22481
|
entity |
| Predicate | brandPortfolio |
P12124
|
FINISHED |
| Object | Engadget |
E66252
|
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: Engadget | Statement: [Oath Inc., brandPortfolio, Engadget]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Engadget Context triple: [Oath Inc., brandPortfolio, Engadget]
-
A.
Engadget
chosen
Engadget is a technology news and reviews website that covers consumer electronics, gadgets, and digital culture.
-
B.
Autoblog
Autoblog is an automotive news and review website known for its coverage of car industry news, vehicle reviews, and consumer car-buying information.
-
C.
Tech
The Tech is a river in southern France that flows through the Pyrénées-Orientales in the Occitanie region before emptying into the Mediterranean Sea.
-
D.
TechCrunch
TechCrunch is a leading technology news website and media platform known for its coverage of startups, Silicon Valley, and the tech industry.
-
E.
ESPNews
ESPNews is an American cable sports television channel owned by ESPN that focuses on sports news, highlights, and analysis.
- 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_69a493d91478819094cc01fb65564bc1 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bb71e7f88190bf33bbe5ef2c68ff |
completed | March 1, 2026, 10:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac429ad45481908641fcaf72f7d1b9 |
completed | March 7, 2026, 3:22 p.m. |
Created at: March 1, 2026, 7:42 p.m.