Triple
T18105651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hawaiian Kingdom cabinet ministers |
E433339
|
entity |
| Predicate | positionHeldBy |
P8
|
FINISHED |
| Object |
Keoni Ana
Keoni Ana was a prominent 19th-century Hawaiian statesman who served as a leading government official and advisor in the Kingdom of Hawaii.
|
E1306381
|
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: Keoni Ana | Statement: [Hawaiian Kingdom cabinet ministers, positionHeldBy, Keoni Ana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Keoni Ana Context triple: [Hawaiian Kingdom cabinet ministers, positionHeldBy, Keoni Ana]
-
A.
Kaiann Drance
Kaiann Drance is a senior Apple executive who frequently appears in product launch events to present and explain new iPhone features.
-
B.
Kalani Sitake
Kalani Sitake is an American football coach best known as the head coach of Brigham Young University's BYU Cougars football program.
-
C.
Christine Kangaloo
Christine Kangaloo is a Trinidad and Tobago politician and attorney who serves as the country's president, having previously held roles such as Senate President and acting President.
-
D.
Kye
Kye is a given name that serves as an alternative spelling of the name Kai.
-
E.
Kori Rae
Kori Rae is a film producer best known for her work at Pixar Animation Studios, including producing the animated feature "Monsters University."
- 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: Keoni Ana Triple: [Hawaiian Kingdom cabinet ministers, positionHeldBy, Keoni Ana]
Generated description
Keoni Ana was a prominent 19th-century Hawaiian statesman who served as a leading government official and advisor in the Kingdom of Hawaii.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Keoni Ana Target entity description: Keoni Ana was a prominent 19th-century Hawaiian statesman who served as a leading government official and advisor in the Kingdom of Hawaii.
-
A.
Kaiann Drance
Kaiann Drance is a senior Apple executive who frequently appears in product launch events to present and explain new iPhone features.
-
B.
Kalani Sitake
Kalani Sitake is an American football coach best known as the head coach of Brigham Young University's BYU Cougars football program.
-
C.
Christine Kangaloo
Christine Kangaloo is a Trinidad and Tobago politician and attorney who serves as the country's president, having previously held roles such as Senate President and acting President.
-
D.
Kye
Kye is a given name that serves as an alternative spelling of the name Kai.
-
E.
Kori Rae
Kori Rae is a film producer best known for her work at Pixar Animation Studios, including producing the animated feature "Monsters University."
- 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddb9981c8190b33697fbcaa901b3 |
completed | April 19, 2026, 1:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a037c36eea4819089619fd895c05893 |
completed | May 12, 2026, 7:15 p.m. |
| NEDg | Description generation | batch_6a037e2086708190af48c53800a729fd |
completed | May 12, 2026, 7:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a037eba5fb88190b2c131260f28df84 |
completed | May 12, 2026, 7:25 p.m. |
Created at: April 10, 2026, 10:28 a.m.