Triple
T19508784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LastPass |
E488093
|
entity |
| Predicate | supportsImportFrom |
P8463
|
FINISHED |
| Object | 1Password |
—
|
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: 1Password | Statement: [LastPass, supportsImportFrom, 1Password]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 1Password Context triple: [LastPass, supportsImportFrom, 1Password]
-
A.
1Password
chosen
1Password is a popular cross-platform password manager that securely stores and autofills passwords, payment details, and other sensitive information for individuals and teams.
-
B.
Bitwarden
Bitwarden is an open-source, cross-platform password manager that securely stores and syncs passwords and other sensitive data across devices.
-
C.
LastPass
LastPass is a popular cloud-based password manager that securely stores and autofills users’ login credentials across devices.
-
D.
iCloud Keychain
iCloud Keychain is Apple’s built-in password and secure information manager that syncs and autofills credentials, Wi‑Fi logins, and payment details across a user’s Apple devices.
-
E.
OnePass
OnePass was Continental Airlines’ frequent flyer loyalty program that allowed passengers to earn and redeem miles for flights and travel rewards.
- 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.