Triple
T6629670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrea Sachs |
E149889
|
entity |
| Predicate | loveInterest |
P7325
|
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: [Andrea Sachs, loveInterest, Nate]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nate Context triple: [Andrea Sachs, loveInterest, 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.
Nate
Nate is the Allied reporting name for the Nakajima Ki-27, a Japanese single-engine fighter aircraft used extensively by the Imperial Japanese Army Air Service in the late 1930s and early World War II.
-
D.
Nathan
Nathan is the given first name of the American writer and poet Jean Toomer, known for his modernist work "Cane."
-
E.
Nathan
Nathan is a prophet in the Hebrew Bible known for advising King David and courageously confronting him over his sin with Bathsheba.
- 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_69c687ee50048190aa151765bef16193 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6afa5c9b48190b645be96d446d0ca |
completed | March 27, 2026, 4:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cbeb04348190957b8e5f098b72bf |
completed | March 27, 2026, 6:26 p.m. |
Created at: March 27, 2026, 1:59 p.m.