Triple
T16021491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kate Burroughs |
E388607
|
entity |
| Predicate | hasName |
P744
|
FINISHED |
| Object | Kate Burroughs |
E388607
|
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: Kate Burroughs | Statement: [Kate Burroughs, hasName, Kate Burroughs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kate Burroughs Context triple: [Kate Burroughs, hasName, Kate Burroughs]
-
A.
Kate Burroughs
chosen
Kate Burroughs is the central protagonist of the film "The Four Seasons," around whom the story’s relationships and events revolve.
-
B.
Kate Healey
Kate Healey is a notable individual recognized as a prominent bearer of the Healey surname.
-
C.
Lindsay Burdge
Lindsay Burdge is an American independent film actress known for her intense, emotionally complex performances in arthouse dramas.
-
D.
Rachel Brooks
Rachel Brooks is a recurring character on the TV series "Justified," known for being a principled and capable deputy U.S. Marshal working alongside Raylan Givens.
-
E.
Anna Holtz
Anna Holtz is a fictional young music copyist and aspiring composer who works closely with Ludwig van Beethoven in the film "Copying Beethoven."
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e183231f2c81908f4e4037c3aa180b |
completed | April 17, 2026, 12:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00077c8e2881909a11a4c53691d187 |
completed | May 10, 2026, 4:20 a.m. |
Created at: April 10, 2026, 4:55 a.m.