Triple
T10667821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nathan Appleton |
E251402
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Nathan |
E441826
|
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: Nathan | Statement: [Nathan Appleton, givenName, Nathan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nathan Context triple: [Nathan Appleton, givenName, Nathan]
-
A.
Nathan
Nathan is a prophet in the Hebrew Bible known for advising King David and courageously confronting him over his sin with Bathsheba.
-
B.
Nathan
Nathan is the central character of Gotthold Ephraim Lessing’s play "Nathan the Wise," portrayed as a wise and compassionate Jewish merchant who advocates religious tolerance and humanism.
-
C.
Nathan
Nathan is the given first name of the American writer and poet Jean Toomer, known for his modernist work "Cane."
-
D.
Nathan
chosen
Nathan is a common given name used in various cultures, often derived from Hebrew meaning "he gave" or "gift."
-
E.
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.
- 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_69d6aa5b0d2881909584b20efc5877f0 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6f860790c81909c2c1d3c489ec5b4 |
completed | April 9, 2026, 12:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d97a9ceea08190944354d127f2c73b |
completed | April 10, 2026, 10:33 p.m. |
Created at: April 8, 2026, 9:08 p.m.