Triple
T1203258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sam Altman |
E25829
|
entity |
| Predicate | investedIn |
P17330
|
FINISHED |
| Object |
E119419
|
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: Pinterest | Statement: [Sam Altman, investedIn, Pinterest]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pinterest Context triple: [Sam Altman, investedIn, Pinterest]
-
A.
Pinterest
chosen
Pinterest is a visual discovery and bookmarking platform where users save and organize images and ideas into themed collections called boards.
-
B.
del.icio.us
del.icio.us was a pioneering social bookmarking web service that allowed users to save, tag, and share links online.
-
C.
Instagram
Instagram is a popular photo and video sharing social media platform known for its visual content, stories, and influencer culture.
-
D.
Tumblr
Tumblr is a microblogging and social networking platform known for its highly customizable blogs, fandom communities, and viral multimedia content.
-
E.
Diigo
Diigo is a social bookmarking and web annotation service that lets users save, tag, highlight, and share online resources.
- 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bdbda0b081909c0147121a945e27 |
completed | March 1, 2026, 10:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac7f3caed481908e9e4b6b9daa544d |
completed | March 7, 2026, 7:40 p.m. |
Created at: March 1, 2026, 7:46 p.m.