Triple
T364458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jobs |
E7927
|
entity |
| Predicate | notableFamily |
P1481
|
FINISHED |
| Object | Jobs family |
E7927
|
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: Jobs family | Statement: [Jobs, notableFamily, Jobs family]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jobs family Context triple: [Jobs, notableFamily, Jobs family]
-
A.
Jobs
chosen
Jobs is the surname of Steve Jobs, the influential co-founder and longtime leader of Apple Inc.
-
B.
Jobes
Jobes is an alternative spelling variant of the surname Jobs, most notably associated by similarity with Apple co-founder Steve Jobs.
-
C.
CAREER
CAREER is a prestigious National Science Foundation program that supports early-career faculty in building a foundation for a lifetime of leadership in research and education.
-
D.
Home Office
The Home Office is a major UK government department responsible for immigration, security, and law and order, including policing and counter-terrorism.
-
E.
LinkedIn
LinkedIn is a professional networking platform and social media service focused on careers, business connections, and job opportunities.
- 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebe6c1b4819083335e880c205ed6 |
completed | Feb. 28, 2026, 1:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3eca938988190b4490e086f25474e |
completed | March 1, 2026, 7:37 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.