Triple
T1611482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | InMail |
E34623
|
entity |
| Predicate | platform |
P1292
|
FINISHED |
| Object |
E5698
|
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: LinkedIn | Statement: [InMail, platform, LinkedIn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LinkedIn Context triple: [InMail, platform, LinkedIn]
-
A.
LinkedIn
chosen
LinkedIn is a professional networking platform and social media service focused on careers, business connections, and job opportunities.
-
B.
ZipRecruiter
ZipRecruiter is an online employment marketplace that connects employers with job seekers through a large job board and AI-driven matching tools.
-
C.
Glassdoor
Glassdoor is an online platform where employees and former employees anonymously review companies, share salary information, and browse job listings.
-
D.
Jobs
Jobs is the surname of Steve Jobs, the influential co-founder and longtime leader of Apple Inc.
-
E.
People Hub
People Hub is a central contact and social networking hub in Windows Phone that aggregates contacts, social feeds, and communication history into a unified interface.
- 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_69a885ffc5ec819091afa325d5f9611c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa622b9fbc8190bff82acdde10deb6 |
completed | March 6, 2026, 5:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adbf3ffc4081909197690046d8ff22 |
completed | March 8, 2026, 6:26 p.m. |
Created at: March 4, 2026, 7:28 p.m.