Triple
T1186013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Thiel |
E25246
|
entity |
| Predicate | notableInvestment |
P3488
|
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: [Peter Thiel, notableInvestment, LinkedIn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LinkedIn Context triple: [Peter Thiel, notableInvestment, LinkedIn]
-
A.
LinkedIn
chosen
LinkedIn is a professional networking platform and social media service focused on careers, business connections, and job opportunities.
-
B.
Glassdoor
Glassdoor is an online platform where employees and former employees anonymously review companies, share salary information, and browse job listings.
-
C.
Jobs
Jobs is the surname of Steve Jobs, the influential co-founder and longtime leader of Apple Inc.
-
D.
MIT Alumni Pool
MIT Alumni Pool is an indoor swimming facility on the MIT campus that serves students, alumni, and the broader community for recreation, training, and aquatic programs.
-
E.
Behance
Behance is an online platform for showcasing and discovering creative work, widely used by designers, artists, and other visual professionals.
- 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_69a49427d98881908646d6c63b8cea1e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd53e4b48190abb2167f8074a6bc |
completed | March 1, 2026, 10:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac6f239a288190ae488d11cff8ebf2 |
completed | March 7, 2026, 6:32 p.m. |
Created at: March 1, 2026, 7:45 p.m.