Triple
T13364133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kim Boggs |
E318893
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Kim
Kim is a common given name used for people of any gender in various cultures, often as a short form of names like Kimberly or Kimball.
|
E1036925
|
NE FINISHED |
How this triple was built (4 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: [Kim Boggs, givenName, Kim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kim Context triple: [Kim Boggs, givenName, 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
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. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kim Triple: [Kim Boggs, givenName, Kim]
Generated description
Kim is a common given name used for people of any gender in various cultures, often as a short form of names like Kimberly or Kimball.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kim Target entity description: Kim is a common given name used for people of any gender in various cultures, often as a short form of names like Kimberly or Kimball.
-
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
Kim is the given name of American singer-songwriter Kim Carnes, best known for her hit song "Bette Davis Eyes."
-
D.
Kim
Kim is a Dutch former field hockey player known for her prolific goal-scoring as a forward on the Netherlands national team.
-
E.
Kim
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.
- F. None of above. chosen
Provenance (5 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_69d806b7bbac8190b85278c87fa7aff3 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69da628c71ac81908cfa36342077766e |
completed | April 11, 2026, 3:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7267e9d608190b36f58a92d4a9964 |
completed | May 3, 2026, 10:42 a.m. |
| NEDg | Description generation | batch_69f72807bae081909f7e66657c03b841 |
completed | May 3, 2026, 10:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f728afff888190a82e3d4f4fad717b |
completed | May 3, 2026, 10:51 a.m. |
Created at: April 9, 2026, 9:32 p.m.