Triple
T11931827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kimball O'Hara |
E283932
|
entity |
| Predicate | protagonistOf |
P9202
|
FINISHED |
| Object | Kim |
E281218
|
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: Kim | Statement: [Kimball O'Hara, protagonistOf, Kim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kim Context triple: [Kimball O'Hara, protagonistOf, Kim]
-
A.
Kim
Kim is a common Korean surname shared by many notable figures in Korean history and contemporary society.
-
B.
Kim
Kim is the commonly used nickname of Kim Philby, the infamous British intelligence officer who became a high-ranking Soviet double agent during the Cold War.
-
C.
Kim
chosen
Kim is a classic adventure novel by Rudyard Kipling that follows an orphaned boy’s coming-of-age amid espionage and cultural crossroads in British-ruled India.
-
D.
Kim
Kim is a character in the horror film "Don't Be Afraid of the Dark," involved in the story’s supernatural and suspenseful events.
-
E.
Kim
Kim is a supporting character in the psychological horror film "It Comes at Night," involved in the tense, paranoia-driven dynamics between two families during a mysterious apocalyptic outbreak.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90305015c81908edb0d9d3d012b2e |
completed | April 10, 2026, 2:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f458a576fc8190b68b27365cd53caf |
completed | May 1, 2026, 7:39 a.m. |
Created at: April 8, 2026, 9:45 p.m.