Triple
T7117781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peggy O’Neal |
E165862
|
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 O’Neal, givenName, Peggy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peggy Context triple: [Peggy O’Neal, givenName, Peggy]
-
A.
Peggy
chosen
Peggy is a common diminutive or nickname for the given name Margaret.
-
B.
Peggy Preston
Peggy Preston is a fictional character from the British drama film "The Dig," which explores the 1939 Sutton Hoo archaeological excavation.
-
C.
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.
-
D.
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.
-
E.
Phyllis
Phyllis is a 1970s American television sitcom, spun off from The Mary Tyler Moore Show, that stars Cloris Leachman as the widowed Phyllis Lindstrom starting a new life in San Francisco.
- 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_69c6888227bc8190a1394679e3116f90 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e618bdac8190be291468b7d977bb |
completed | March 27, 2026, 8:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7b8d92fec8190bd275023bdef8e08 |
completed | March 28, 2026, 11:17 a.m. |
Created at: March 27, 2026, 2:43 p.m.