Triple
T8267294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lesley Stahl |
E193332
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Lesley |
E713641
|
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: Lesley | Statement: [Lesley Stahl, givenName, Lesley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lesley Context triple: [Lesley Stahl, givenName, Lesley]
-
A.
Lesley
chosen
Lesley is the given name of English soprano and media personality Lesley Garrett.
-
B.
Leslie
Leslie is the middle name of early 20th-century Major League Baseball pitcher Hippo Vaughn, a standout left-hander best known for his time with the Chicago Cubs.
-
C.
Leslie
Leslie is the given name of Leslie R. Groves Jr., the U.S. Army Corps of Engineers officer who directed the Manhattan Project during World War II.
-
D.
Leslie
Leslie is the given name of American actress and singer Leslie Uggams, known for her work on stage, television, and film.
-
E.
Leslie
Leslie is a given name used for people of any gender in English-speaking countries.
- 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_69ca82e081d48190986beaa51f498ab9 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb794fc4208190b268bc69ff2b28a9 |
completed | March 31, 2026, 7:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd6833065c8190945e88022ad2869d |
completed | April 1, 2026, 6:47 p.m. |
Created at: March 30, 2026, 5:50 p.m.