Triple
T6038606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacqueline |
E134483
|
entity |
| Predicate | relatedToName |
P3889
|
FINISHED |
| Object | Jaclyn |
E134483
|
NE FINISHED |
How this triple was built (2 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: Jaclyn | Statement: [Jacqueline, relatedToName, Jaclyn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jaclyn Context triple: [Jacqueline, relatedToName, Jaclyn]
-
A.
Jenna
Jenna is a common feminine given name, often used as a diminutive or variant of Jennifer.
-
B.
Jocelyn
Jocelyn is a given name commonly used for people of any gender, often associated with the nickname "Jo."
-
C.
Jacqueline
chosen
Jacqueline is a feminine given name most famously borne by former U.S. First Lady Jacqueline Kennedy Onassis.
-
D.
Madelyn
Madelyn is a feminine given name, often considered a modern variant of Madeline and commonly used in English-speaking countries.
-
E.
Carolyn
Carolyn Bessette-Kennedy was an American publicist and style icon best known as the wife of John F. Kennedy Jr.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c00875db5c819099dd5bb833ec43c2 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056ccac948190a27547878d4db8e4 |
completed | March 22, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11cfbb4cc81909736d5d041dd0b23 |
completed | March 23, 2026, 10:59 a.m. |
Created at: March 22, 2026, 4:08 p.m.