Triple
T1917048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth |
E40040
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object |
Betsy
Betsy is a common diminutive or nickname for the given name Elizabeth.
|
E220459
|
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: Betsy | Statement: [Elizabeth, hasVariant, Betsy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Betsy Context triple: [Elizabeth, hasVariant, Betsy]
-
A.
Betsy
Betsy is a key female character in the 1976 film "Taxi Driver," known as the idealistic campaign worker who becomes the object of Travis Bickle’s fixation.
-
B.
Martha
Martha is a feminine given name of Aramaic origin, historically borne by notable figures such as Martha Washington, the first First Lady of the United States.
-
C.
Mary Ann
Mary Ann is the namesake of the city of Marianna in Florida.
-
D.
Abigail
Abigail is a feminine given name of Hebrew origin meaning "my father is joy," historically popular in English-speaking countries.
-
E.
Betty
Betty is a minor character in Enid Blyton’s "Malory Towers" series, known as a lively and mischievous schoolgirl at the boarding school.
- 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: Betsy Triple: [Elizabeth, hasVariant, Betsy]
Generated description
Betsy is a common diminutive or nickname for the given name Elizabeth.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Betsy Target entity description: Betsy is a common diminutive or nickname for the given name Elizabeth.
-
A.
Betsy
Betsy is a key female character in the 1976 film "Taxi Driver," known as the idealistic campaign worker who becomes the object of Travis Bickle’s fixation.
-
B.
Martha
Martha is a feminine given name of Aramaic origin, historically borne by notable figures such as Martha Washington, the first First Lady of the United States.
-
C.
Mary Ann
Mary Ann is the namesake of the city of Marianna in Florida.
-
D.
Abigail
Abigail is a feminine given name of Hebrew origin meaning "my father is joy," historically popular in English-speaking countries.
-
E.
Betty
Betty is a minor character in Enid Blyton’s "Malory Towers" series, known as a lively and mischievous schoolgirl at the boarding school.
- 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_69a8864298748190a2f2fd34f7ef8d77 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb20f54848190b9457e1231aa49db |
completed | March 7, 2026, 5:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfbae5760819083c046d0941513de |
completed | March 8, 2026, 10:43 p.m. |
| NEDg | Description generation | batch_69adfc50a3488190afe44ee5125d9ebd |
completed | March 8, 2026, 10:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adfcdccce48190a2591b90c81ad084 |
completed | March 8, 2026, 10:49 p.m. |
Created at: March 4, 2026, 7:35 p.m.