Triple
T19508722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LastPass |
E488093
|
entity |
| Predicate | developer |
P73
|
FINISHED |
| Object | LastPass US LP |
—
|
NE NERFINISHED |
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: LastPass US LP | Statement: [LastPass, developer, LastPass US LP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LastPass US LP Context triple: [LastPass, developer, LastPass US LP]
-
A.
LastPass
chosen
LastPass is a popular cloud-based password manager that securely stores and autofills users’ login credentials across devices.
-
B.
1Password
1Password is a popular cross-platform password manager that securely stores and autofills passwords, payment details, and other sensitive information for individuals and teams.
-
C.
OnePass
OnePass was Continental Airlines’ frequent flyer loyalty program that allowed passengers to earn and redeem miles for flights and travel rewards.
-
D.
Bitwarden
Bitwarden is an open-source, cross-platform password manager that securely stores and syncs passwords and other sensitive data across devices.
-
E.
Duo Security
Duo Security is a cybersecurity company best known for its cloud-based multi-factor authentication and zero-trust access solutions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6351426448190aec1ee26c09faa24 |
completed | April 20, 2026, 2:15 p.m. |
Created at: April 10, 2026, 1:40 p.m.