Triple
T6757713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Nathaniel Showalter III |
E154503
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Showalter
Showalter is a surname of German origin borne by various notable individuals across fields such as sports, academia, and the arts.
|
E617931
|
NE FINISHED |
How this triple was built (4 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: Showalter | Statement: [William Nathaniel Showalter III, familyName, Showalter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Showalter Context triple: [William Nathaniel Showalter III, familyName, Showalter]
-
A.
Sharston
Sharston is a suburban area of Manchester, England, known for its residential neighborhoods and proximity to other districts like Baguley and Wythenshawe.
-
B.
Lacedelli
Lacedelli is an Italian surname most notably associated with Lino Lacedelli, one of the first climbers to reach the summit of K2.
-
C.
Finklea
Finklea is the birth surname of American actress and dancer Cyd Charisse, known for her roles in classic Hollywood musicals.
-
D.
Tuthill
Tuthill is a surname most notably associated with William Burnet Tuthill, the American architect who designed Carnegie Hall in New York City.
-
E.
Kniphausen
Kniphausen is a historical territory in present-day Germany that once functioned as a small semi-independent lordship under various regional powers.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Showalter Triple: [William Nathaniel Showalter III, familyName, Showalter]
Generated description
Showalter is a surname of German origin borne by various notable individuals across fields such as sports, academia, and the arts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Showalter Target entity description: Showalter is a surname of German origin borne by various notable individuals across fields such as sports, academia, and the arts.
-
A.
Sharston
Sharston is a suburban area of Manchester, England, known for its residential neighborhoods and proximity to other districts like Baguley and Wythenshawe.
-
B.
Lacedelli
Lacedelli is an Italian surname most notably associated with Lino Lacedelli, one of the first climbers to reach the summit of K2.
-
C.
Finklea
Finklea is the birth surname of American actress and dancer Cyd Charisse, known for her roles in classic Hollywood musicals.
-
D.
Tuthill
Tuthill is a surname most notably associated with William Burnet Tuthill, the American architect who designed Carnegie Hall in New York City.
-
E.
Kniphausen
Kniphausen is a historical territory in present-day Germany that once functioned as a small semi-independent lordship under various regional powers.
- F. None of above. chosen
Provenance (5 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_69c6880fd5808190be684854081e27dd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d1f76c9c81908c213772a54f1352 |
completed | March 27, 2026, 6:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c712ad568c8190bc82f6149c22273a |
completed | March 27, 2026, 11:28 p.m. |
| NEDg | Description generation | batch_69c713b3accc81908d19c1b00e2c312c |
completed | March 27, 2026, 11:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7146413748190b844d9422dce42c2 |
completed | March 27, 2026, 11:36 p.m. |
Created at: March 27, 2026, 2:11 p.m.