Triple
T21652662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Varjak |
E534376
|
entity |
| Predicate | romanticInterest |
P7325
|
FINISHED |
| Object | Holly Golightly |
—
|
NE NERFINISHED |
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: Holly Golightly | Statement: [Paul Varjak, romanticInterest, Holly Golightly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Holly Golightly Context triple: [Paul Varjak, romanticInterest, Holly Golightly]
-
A.
Jane Golightly
Jane Golightly was the wife of pioneering English steam locomotive engineer Timothy Hackworth.
-
B.
character Holly Golightly
chosen
Holly Golightly is the charming, free-spirited New York socialite and central heroine of Truman Capote’s novella "Breakfast at Tiffany’s" and its iconic film adaptation.
-
C.
Nola Darling
Nola Darling is a free-spirited, independent Brooklyn artist known for her unapologetic approach to sexuality and relationships in Spike Lee’s work.
-
D.
Charlotte Hollis
Charlotte Hollis is the troubled Southern heiress at the center of the psychological thriller film "Hush...Hush, Sweet Charlotte," portrayed by Bette Davis.
-
E.
Golightly
Golightly is a surname of English origin, most famously associated with the fictional character Holly Golightly from Truman Capote’s novella "Breakfast at Tiffany’s."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c466aec88190ba39c7543dbc8ba2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef591594a08190bf0ddd0a0c0922ba |
completed | April 27, 2026, 12:39 p.m. |
Created at: April 16, 2026, 6:36 p.m.