Triple
T498764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Lou Jepsen |
E10352
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object |
E1582
|
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: Facebook | Statement: [Mary Lou Jepsen, employer, Facebook]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Facebook Context triple: [Mary Lou Jepsen, employer, Facebook]
-
A.
Facebook
chosen
Facebook is a major global social networking platform that allows users to connect, share content, and communicate online.
-
B.
Meta Platforms, Inc.
Meta Platforms, Inc. is a major American technology company best known as the parent of Facebook, Instagram, WhatsApp, and other social media and virtual reality products.
-
C.
MySpace
MySpace is a pioneering early-2000s social networking website that allowed users to create customizable profile pages, connect with friends, and share music and other media.
-
D.
Instagram
Instagram is a popular photo and video sharing social media platform known for its visual content, stories, and influencer culture.
-
E.
Snap Inc.
Snap Inc. is an American technology and social media company best known for developing the multimedia messaging app Snapchat and related camera and augmented reality products.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f119b14c8190a5a6b119579c2682 |
completed | Feb. 28, 2026, 1:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a481efc3a881909575c5981e13a16b |
completed | March 1, 2026, 6:14 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.