Triple
T3444958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steve Jobs |
E72653
|
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: [Steve Jobs, familyName, Jobs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jobs Context triple: [Steve Jobs, familyName, Jobs]
-
A.
Jobs
chosen
Jobs is the surname of Steve Jobs, the influential co-founder and longtime leader of Apple Inc.
-
B.
Jobs
Jobs is a 2013 biographical drama film depicting the life and career of Apple co-founder Steve Jobs.
-
C.
ZipRecruiter
ZipRecruiter is an online employment marketplace that connects employers with job seekers through a large job board and AI-driven matching tools.
-
D.
GrabMart
GrabMart is an on-demand online grocery and everyday essentials delivery service operated by Southeast Asian super-app Grab.
-
E.
Vueltabajo
Vueltabajo is a renowned tobacco-growing region in western Cuba, famous for producing some of the world’s finest cigar tobacco.
- 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_69ad85b05c848190b7a28ceec2bd7b74 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adba2b93dc819094e9cca1a5d9540a |
completed | March 8, 2026, 6:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b360deda448190a63a39688be2dbfb |
completed | March 13, 2026, 12:57 a.m. |
Created at: March 8, 2026, 3:16 p.m.