Triple
T9705467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marco Arment |
E234886
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Instapaper |
E815193
|
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: Instapaper | Statement: [Marco Arment, notableWork, Instapaper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Instapaper Context triple: [Marco Arment, notableWork, Instapaper]
-
A.
Instapaper
chosen
Instapaper is a read-it-later service and app that lets users save web articles for offline reading in a clean, distraction-free format.
-
B.
Feedly
Feedly is a popular web-based RSS and news aggregator that gained prominence as a primary alternative after the shutdown of Google Reader.
-
C.
Evernote
Evernote is a cross-platform note-taking and organization application that lets users capture, sync, and manage text, images, and other content across devices.
-
D.
Pinboard
Pinboard is a minimalist, subscription-based social bookmarking service known for its fast, no-frills interface and emphasis on privacy and long-term archiving of saved links.
-
E.
Flipboard
Flipboard is a personalized news and content aggregation app that presents articles, videos, and social media updates in a magazine-style layout for mobile and web users.
- 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_69ca84cc78808190a56f3402b7c139a7 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9da369b4819081f6ce01289ed725 |
completed | April 1, 2026, 10:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bcc0117c8190bc82a985ce59623d |
completed | April 5, 2026, 1:37 a.m. |
Created at: March 30, 2026, 8:19 p.m.