Triple
T1833617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nathaniel |
E41013
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object |
Nate
Nate is a common diminutive form of the given name Nathaniel, often used as a casual or familiar nickname.
|
E210768
|
NE FINISHED |
How this triple was built (4 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: [Nathaniel, hasDiminutive, Nate]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nate Context triple: [Nathaniel, hasDiminutive, 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.
Nathan
Nathan is a prophet in the Hebrew Bible known for advising King David and courageously confronting him over his sin with Bathsheba.
-
C.
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.
-
D.
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.
-
E.
Nate Heller
Nate Heller is a film composer and songwriter known for his emotionally resonant scores for movies such as "A Beautiful Day in the Neighborhood" and "Can You Ever Forgive Me?".
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nate Triple: [Nathaniel, hasDiminutive, Nate]
Generated description
Nate is a common diminutive form of the given name Nathaniel, often used as a casual or familiar nickname.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nate Target entity description: Nate is a common diminutive form of the given name Nathaniel, often used as a casual or familiar nickname.
-
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.
Nathan
Nathan is a prophet in the Hebrew Bible known for advising King David and courageously confronting him over his sin with Bathsheba.
-
C.
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.
-
D.
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.
-
E.
Nate Heller
Nate Heller is a film composer and songwriter known for his emotionally resonant scores for movies such as "A Beautiful Day in the Neighborhood" and "Can You Ever Forgive Me?".
- F. None of above. chosen
Provenance (5 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_69a88647f9388190909bc36e795bdaec |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb02540dc819081b19a09562139cd |
completed | March 7, 2026, 4:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69addf45fcd08190a82a4057470eb3ee |
completed | March 8, 2026, 8:42 p.m. |
| NEDg | Description generation | batch_69ade34a51b88190937437a1856557c8 |
completed | March 8, 2026, 8:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ade3e2625c81909df2b22ce4cbf3ff |
completed | March 8, 2026, 9:02 p.m. |
Created at: March 4, 2026, 7:33 p.m.