Triple
T1611520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | InMail |
E34623
|
entity |
| Predicate | integratedWith |
P2830
|
FINISHED |
| Object | LinkedIn profiles |
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 profiles | Statement: [InMail, integratedWith, LinkedIn profiles]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LinkedIn profiles Context triple: [InMail, integratedWith, LinkedIn profiles]
-
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.
CV
CV is a common abbreviation for Chula Vista, a coastal city in Southern California located just south of San Diego.
-
D.
Glassdoor
Glassdoor is an online platform where employees and former employees anonymously review companies, share salary information, and browse job listings.
-
E.
C.V.
C.V. is the autobiographical section of Stephen King’s book "On Writing," in which he recounts key experiences from his life that shaped him as a writer.
- 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_69add1ac4b9c8190a7d0fa610a77f9c3 |
completed | March 8, 2026, 7:44 p.m. |
Created at: March 4, 2026, 7:28 p.m.