Triple
T8704986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chief Technology Officer of LinkedIn |
E206625
|
entity |
| Predicate | employer |
P7
|
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: [Chief Technology Officer of LinkedIn, employer, LinkedIn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LinkedIn Context triple: [Chief Technology Officer of LinkedIn, employer, 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.
workforce1 Career Centers network
The Workforce1 Career Centers network is a system of New York City career centers that connect job seekers with employment opportunities, training, and related workforce development services.
-
E.
CareerBuilder (stake)
CareerBuilder (stake) refers to the ownership interest held in CareerBuilder, a major online employment and recruitment platform.
- 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_69ca835645e881908f00e3c8b51da81d |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc58fb43f081909df5d1e31cb1ec04 |
completed | March 31, 2026, 11:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cef423b1c4819081ea887af8f8e576 |
completed | April 2, 2026, 10:56 p.m. |
Created at: March 30, 2026, 6:34 p.m.