Triple
T12282081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drew Houston |
E292737
|
entity |
| Predicate | boardMemberOf |
P10
|
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: [Drew Houston, boardMemberOf, Facebook]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Facebook Context triple: [Drew Houston, boardMemberOf, Facebook]
-
A.
Facebook
chosen
Facebook is a major global social networking platform that allows users to connect, share content, and communicate online.
-
B.
Facebook Portal
Facebook Portal is a line of smart video-calling devices developed by Meta (formerly Facebook), designed to facilitate hands-free, AI-enhanced communication in the home.
-
C.
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.
-
D.
Bebo
Bebo is a now-defunct social networking website that was especially popular in the mid-2000s for sharing profiles, photos, and messages among friends.
-
E.
FB
FB is the common abbreviation for Fenerbahçe SK, one of Turkey’s most prominent multi-sport clubs best known for its successful football team based in Istanbul.
- 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cf2b09c81908a11581d33f65be0 |
completed | April 10, 2026, 3:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e6799088190a5644267733ca2e5 |
completed | May 2, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:52 p.m.