Triple
T2016600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonathan |
E44008
|
entity |
| Predicate | shortForm |
P43
|
FINISHED |
| Object | Nate |
E210768
|
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: Nate | Statement: [Jonathan, shortForm, Nate]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nate Context triple: [Jonathan, shortForm, Nate]
-
A.
Nate
Nate is a central fictional character in Margaret Atwood’s novel "Life Before Man," around whom much of the story’s emotional and relational tension revolves.
-
B.
Nate
chosen
Nate is a common diminutive form of the given name Nathaniel, often used as a casual or familiar nickname.
-
C.
Nathan
Nathan is a prophet in the Hebrew Bible known for advising King David and courageously confronting him over his sin with Bathsheba.
-
D.
Nate Cooper
Nate Cooper is a character in the film "The Devil Wears Prada," known as the boyfriend of protagonist Andy Sachs who represents her pre-fashion-world life and values.
-
E.
Nate Rogers
Nate Rogers is a notable individual who shares the Rogers surname and has achieved enough recognition to be specifically identified among its bearers.
- 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_69a8891201bc8190aca837be6de41579 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb8ccdb7c81909f6b3c96f79fcdfc |
completed | March 7, 2026, 5:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae0aef0fe88190adf9cd218cf7d8b4 |
completed | March 8, 2026, 11:49 p.m. |
Created at: March 4, 2026, 7:38 p.m.