Triple
T78892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject |
E1582
|
entity | |
| Predicate | formerName |
P65
|
FINISHED |
| Object | TheFacebook |
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: TheFacebook | Statement: [Facebook, formerName, TheFacebook]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TheFacebook Context triple: [Facebook, formerName, TheFacebook]
-
A.
Facebook
chosen
Facebook is a major global social networking platform that allows users to connect, share content, and communicate online.
-
B.
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.
-
C.
Mark Zuckerberg
Mark Zuckerberg is an American technology entrepreneur and philanthropist best known as the co-founder and CEO of Facebook (now Meta Platforms).
-
D.
Tumblr
Tumblr is a microblogging and social networking platform known for its highly customizable blogs, fandom communities, and viral multimedia content.
-
E.
Randi Zuckerberg
Randi Zuckerberg is an American businesswoman, author, and former Facebook marketing executive who founded the media company Zuckerberg Media and focuses on technology, entrepreneurship, and digital literacy.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a24f335b5c8190bf2158d884890ac2 |
completed | Feb. 28, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2981ed378819099ef3fbff2236a94 |
completed | Feb. 28, 2026, 7:24 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.