Triple
T129910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kathleen Kennedy Cavendish |
E2631
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Kathleen
Kathleen is a feminine given name of Irish origin, derived from the name Catherine and widely used in English-speaking countries.
|
E28330
|
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: Kathleen | Statement: [Kathleen Kennedy Cavendish, givenName, Kathleen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kathleen Context triple: [Kathleen Kennedy Cavendish, givenName, Kathleen]
-
A.
Kathy
Kathy is the given name of Kathy Hochul, the 57th governor of New York and the first woman to hold that office.
-
B.
Katherine Hudson
Katherine Hudson was the wife of English explorer Henry Hudson, known primarily through historical records of his voyages and family.
-
C.
Katherine Rogers
Katherine Rogers was the mother of John Harvard, the English clergyman whose bequest helped found Harvard College in colonial Massachusetts.
-
D.
Joanna
Joanna is the first name of Joanna Newsom, an American harpist, singer-songwriter, and musician known for her intricate compositions and distinctive vocal style.
-
E.
Nancy
Nancy is a feminine given name of Hebrew origin meaning "grace" that became especially popular in English-speaking countries in the 20th century.
- 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: Kathleen Triple: [Kathleen Kennedy Cavendish, givenName, Kathleen]
Generated description
Kathleen is a feminine given name of Irish origin, derived from the name Catherine and widely used in English-speaking countries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kathleen Target entity description: Kathleen is a feminine given name of Irish origin, derived from the name Catherine and widely used in English-speaking countries.
-
A.
Kathy
Kathy is the given name of Kathy Hochul, the 57th governor of New York and the first woman to hold that office.
-
B.
Katherine Hudson
Katherine Hudson was the wife of English explorer Henry Hudson, known primarily through historical records of his voyages and family.
-
C.
Katherine Rogers
Katherine Rogers was the mother of John Harvard, the English clergyman whose bequest helped found Harvard College in colonial Massachusetts.
-
D.
Joanna
Joanna is the first name of Joanna Newsom, an American harpist, singer-songwriter, and musician known for her intricate compositions and distinctive vocal style.
-
E.
Nancy
Nancy is a feminine given name of Hebrew origin meaning "grace" that became especially popular in English-speaking countries in the 20th century.
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257845c548190bfb49409988d1c57 |
completed | Feb. 28, 2026, 2:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a34d8edb8c81909c7229fe6e4c0569 |
completed | Feb. 28, 2026, 8:18 p.m. |
| NEDg | Description generation | batch_69a34dfe27a081909498374e791fb725 |
completed | Feb. 28, 2026, 8:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a34ed268f88190a4a4c53bc52a7182 |
completed | Feb. 28, 2026, 8:23 p.m. |
Created at: Feb. 28, 2026, 2:30 a.m.