Triple
T1260982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erin Jobs |
E12498
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Jobs |
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 | Statement: [Erin Jobs, familyName, Jobs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jobs Context triple: [Erin Jobs, familyName, Jobs]
-
A.
Jobs
chosen
Jobs is the surname of Steve Jobs, the influential co-founder and longtime leader of Apple Inc.
-
B.
Vueltabajo
Vueltabajo is a renowned tobacco-growing region in western Cuba, famous for producing some of the world’s finest cigar tobacco.
-
C.
Jobes
Jobes is an alternative spelling variant of the surname Jobs, most notably associated by similarity with Apple co-founder Steve Jobs.
-
D.
Employment Service
Employment Service was a former UK government agency responsible for helping people find work and administering employment-related benefits before its functions were absorbed into successor bodies.
-
E.
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.
- 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_69a4933352e08190ac617291985e76c0 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bfc64e648190b9c4f980eb8168aa |
completed | March 1, 2026, 10:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac93d044bc819091fd0cfa7a957640 |
completed | March 7, 2026, 9:08 p.m. |
Created at: March 1, 2026, 7:50 p.m.