Triple
T12139026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shawn |
E289134
|
entity |
| Predicate | hasRelatedName |
P3889
|
FINISHED |
| Object | Shawna |
E427742
|
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: Shawna | Statement: [Shawn, hasRelatedName, Shawna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shawna Context triple: [Shawn, hasRelatedName, Shawna]
-
A.
Shauna
chosen
Shauna is a feminine given name, commonly considered the female form of Sean and used primarily in English-speaking countries.
-
B.
Shayla
Shayla is a feminine given name, often considered a modern or variant spelling of names like Sheila or Shayla-related forms.
-
C.
Shawna Waldron
Shawna Waldron is an American actress best known for her early roles in films such as "The American President" and the family sports comedy "Little Giants."
-
D.
Shayne
Shayne is a given name, typically used as a variant spelling of Shane.
-
E.
Elana
Elana is a Polish football club based in the city of Toruń.
- 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9158eef48819083bdce283a363414 |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e4a573c8190b5dd6cc61849739b |
completed | May 2, 2026, 3:54 p.m. |
Created at: April 8, 2026, 9:49 p.m.