Triple
T15329882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Kane |
E366504
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object |
Emma Kane
Emma Kane is the daughter of Tom Kane, the powerful and ailing mayor at the center of the television series "Boss."
|
E1150005
|
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: Emma Kane | Statement: [Tom Kane, hasChild, Emma Kane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emma Kane Context triple: [Tom Kane, hasChild, Emma Kane]
-
A.
Chelsea Kane
Chelsea Kane is an American actress and singer best known for her roles on Disney Channel series such as "Jonas" and "Baby Daddy."
-
B.
Daphne Keen
Daphne Keen is a British-Spanish actress best known for her breakout role as Laura/X-23 in the film "Logan" and as Lyra Belacqua in the television series "His Dark Materials."
-
C.
Gemma Craven
Gemma Craven is an Irish-born actress and singer best known for her work in musical theatre and film, including her acclaimed performances on the West End.
-
D.
Rachel Kane
Rachel Kane is a key CIA operative and mission handler in the video game Call of Duty: Black Ops III, guiding and assisting the player throughout much of the campaign.
-
E.
Mary Kane
Mary Kane is a film producer known for her work on the 1990 crime drama "King of New York."
- 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: Emma Kane Triple: [Tom Kane, hasChild, Emma Kane]
Generated description
Emma Kane is the daughter of Tom Kane, the powerful and ailing mayor at the center of the television series "Boss."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Emma Kane Target entity description: Emma Kane is the daughter of Tom Kane, the powerful and ailing mayor at the center of the television series "Boss."
-
A.
Chelsea Kane
Chelsea Kane is an American actress and singer best known for her roles on Disney Channel series such as "Jonas" and "Baby Daddy."
-
B.
Daphne Keen
Daphne Keen is a British-Spanish actress best known for her breakout role as Laura/X-23 in the film "Logan" and as Lyra Belacqua in the television series "His Dark Materials."
-
C.
Gemma Craven
Gemma Craven is an Irish-born actress and singer best known for her work in musical theatre and film, including her acclaimed performances on the West End.
-
D.
Rachel Kane
Rachel Kane is a key CIA operative and mission handler in the video game Call of Duty: Black Ops III, guiding and assisting the player throughout much of the campaign.
-
E.
Mary Kane
Mary Kane is a film producer known for her work on the 1990 crime drama "King of New York."
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e0161ac8190aa1d52c063c02ad0 |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef8b1b2d08190a158bf65535ad750 |
completed | May 9, 2026, 9:04 a.m. |
| NEDg | Description generation | batch_69fefb10ba78819094948f5401702e79 |
completed | May 9, 2026, 9:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fefbad7de08190aa2479ec0243e3a6 |
completed | May 9, 2026, 9:17 a.m. |
Created at: April 10, 2026, 3:17 a.m.