Triple
T23304662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annie Wittenmyer |
E590401
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Wittenmyer
Wittenmyer is a surname most notably associated with Annie Wittenmyer, a 19th-century American social reformer, Civil War relief organizer, and advocate for soldiers’ orphans.
|
E1580913
|
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: Wittenmyer | Statement: [Annie Wittenmyer, familyName, Wittenmyer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wittenmyer Context triple: [Annie Wittenmyer, familyName, Wittenmyer]
-
A.
Donahue
Donahue is a surname most notably associated with American actress Elinor Donahue, known for her roles in classic television series.
-
B.
Michell
Michell is a given name and surname that functions as a variant spelling of Mitchell.
-
C.
Weigert
Weigert is a German-language surname borne by various notable individuals in fields such as science, sports, and the arts.
-
D.
Landé
Landé is a German surname most notably associated with physicist Alfred Landé, known for his contributions to quantum theory and atomic physics.
-
E.
Schisgal
Schisgal is the surname of Murray Schisgal, an American playwright and screenwriter best known for co-writing the film "Tootsie."
- 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: Wittenmyer Triple: [Annie Wittenmyer, familyName, Wittenmyer]
Generated description
Wittenmyer is a surname most notably associated with Annie Wittenmyer, a 19th-century American social reformer, Civil War relief organizer, and advocate for soldiers’ orphans.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wittenmyer Target entity description: Wittenmyer is a surname most notably associated with Annie Wittenmyer, a 19th-century American social reformer, Civil War relief organizer, and advocate for soldiers’ orphans.
-
A.
Donahue
Donahue is a surname most notably associated with American actress Elinor Donahue, known for her roles in classic television series.
-
B.
Michell
Michell is a given name and surname that functions as a variant spelling of Mitchell.
-
C.
Weigert
Weigert is a German-language surname borne by various notable individuals in fields such as science, sports, and the arts.
-
D.
Landé
Landé is a German surname most notably associated with physicist Alfred Landé, known for his contributions to quantum theory and atomic physics.
-
E.
Schisgal
Schisgal is the surname of Murray Schisgal, an American playwright and screenwriter best known for co-writing the film "Tootsie."
- 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_69e25d1c0ecc8190a355aa229f06d0e0 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19725b248819089e61efb82e3440f |
completed | April 29, 2026, 5:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c4c9934ec819094ebbe6e61d18ab7 |
completed | May 19, 2026, 11:42 a.m. |
| NEDg | Description generation | batch_6a0c4f37e390819083df9a959acf3a32 |
completed | May 19, 2026, 11:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c4fdafde88190a7ac791189acde68 |
completed | May 19, 2026, 11:56 a.m. |
Created at: April 17, 2026, 5:04 p.m.