Triple
T1635010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slack |
E35339
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | Slack Huddles |
E35339
|
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: Slack Huddles | Statement: [Slack, hasComponent, Slack Huddles]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Slack Huddles Context triple: [Slack, hasComponent, Slack Huddles]
-
A.
Slack
chosen
Slack is a cloud-based team collaboration and messaging platform widely used for real-time communication, file sharing, and integrations with tools like Google Workspace.
-
B.
Google Chat
Google Chat is a business-focused messaging platform by Google that supports direct messages, group conversations, and integrated collaboration within the Google Workspace ecosystem.
-
C.
Yammer
Yammer is an enterprise social networking service that enables employees within an organization to communicate, collaborate, and share information in a secure, Facebook-like environment.
-
D.
Chatterbug
Chatterbug is an online language-learning platform that offers live tutoring and interactive exercises to help users practice and improve foreign language skills.
-
E.
Microsoft Chat
Microsoft Chat is an early Windows-based chat client from Microsoft that provided graphical, comic-style online conversations using IRC-like services.
- 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90a1679408190a9faa7b22c388c4b |
completed | March 5, 2026, 4:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad58dbd0608190be207ab2bcdc9eef |
completed | March 8, 2026, 11:09 a.m. |
Created at: March 4, 2026, 7:28 p.m.