Triple
T5818101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brennan-Jobs |
E129035
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | Jobs (surname) |
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 (surname) | Statement: [Brennan-Jobs, relatedTo, Jobs (surname)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jobs (surname) Context triple: [Brennan-Jobs, relatedTo, Jobs (surname)]
-
A.
Jobes
Jobes is an alternative spelling variant of the surname Jobs, most notably associated by similarity with Apple co-founder Steve Jobs.
-
B.
Jobs
chosen
Jobs is the surname of Steve Jobs, the influential co-founder and longtime leader of Apple Inc.
-
C.
Jobs
Jobs is a 2013 biographical drama film depicting the life and career of Apple co-founder Steve Jobs.
-
D.
Johns
Johns is a given name most notably associated with Johns Hopkins, the 19th-century American entrepreneur and philanthropist whose endowments founded Johns Hopkins University and Hospital.
-
E.
Jones
Jones is a common English-language surname borne by numerous notable individuals across fields such as entertainment, sports, politics, and science.
- 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_69c0084869e881908d7859492183ca7b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c033e36cbc81908f1ef1a1a310674c |
completed | March 22, 2026, 6:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0985399488190bcab9702e3b88539 |
completed | March 23, 2026, 1:33 a.m. |
Created at: March 22, 2026, 3:53 p.m.