Triple
T10070253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peggy Cripps |
E213602
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Peggy |
E132734
|
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: Peggy | Statement: [Peggy Cripps, givenName, Peggy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peggy Context triple: [Peggy Cripps, givenName, Peggy]
-
A.
Peggy
chosen
Peggy is a common diminutive or nickname for the given name Margaret.
-
B.
Peggy-Ann
Peggy-Ann is a 1926 Broadway musical comedy with lyrics by Lorenz Hart and music by Richard Rodgers.
-
C.
Peggy Preston
Peggy Preston is a fictional character from the British drama film "The Dig," which explores the 1939 Sutton Hoo archaeological excavation.
-
D.
Peggy Sue
"Peggy Sue" is a classic 1957 rock and roll song by Buddy Holly that became one of his most famous and enduring hits.
-
E.
Phyllis
Phyllis is a tragic figure from classical legend, often depicted as a wronged lover who is transformed into an almond tree after being abandoned.
- 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_69ca839add308190b57d53b4ec21f2d0 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdcffa045c8190a08db0bb74cb006a |
completed | April 2, 2026, 2:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d29aa05cc881909f59178e9c6c01ef |
completed | April 5, 2026, 5:23 p.m. |
Created at: March 30, 2026, 8:58 p.m.