Triple
T4282412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erdman Penner |
E97183
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Penner
Penner is a surname of Germanic origin borne by various notable individuals across fields such as entertainment, sports, and academia.
|
E426331
|
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: Penner | Statement: [Erdman Penner, familyName, Penner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Penner Context triple: [Erdman Penner, familyName, Penner]
-
A.
Perron
Perron is a surname of French origin, often considered a variant of the name Perrin.
-
B.
Peenestrom
Peenestrom is a strait in northeastern Germany that connects the Szczecin Lagoon with the Baltic Sea and separates the island of Usedom from the mainland.
-
C.
Arvin
Arvin is a small agricultural city in Southern California’s San Joaquin Valley, known for its farming economy and diverse rural community.
-
D.
Parker
Parker is a common English surname borne by numerous notable individuals across fields such as politics, sports, arts, and science.
-
E.
Menzel
Menzel is the surname of Idina Menzel, the American actress and singer best known for her roles in Broadway musicals and the film "Frozen."
- 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: Penner Triple: [Erdman Penner, familyName, Penner]
Generated description
Penner is a surname of Germanic origin borne by various notable individuals across fields such as entertainment, sports, and academia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Penner Target entity description: Penner is a surname of Germanic origin borne by various notable individuals across fields such as entertainment, sports, and academia.
-
A.
Perron
Perron is a surname of French origin, often considered a variant of the name Perrin.
-
B.
Peenestrom
Peenestrom is a strait in northeastern Germany that connects the Szczecin Lagoon with the Baltic Sea and separates the island of Usedom from the mainland.
-
C.
Arvin
Arvin is a small agricultural city in Southern California’s San Joaquin Valley, known for its farming economy and diverse rural community.
-
D.
Parker
Parker is a common English surname borne by numerous notable individuals across fields such as politics, sports, arts, and science.
-
E.
Menzel
Menzel is the surname of Idina Menzel, the American actress and singer best known for her roles in Broadway musicals and the film "Frozen."
- 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_69b3454595848190a0e6bbb6a2bea040 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3503938f481909505e0a322dd2b6c |
completed | March 12, 2026, 11:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b7bec1a88190bd36ed6d48e1c94e |
completed | March 14, 2026, 7:32 p.m. |
| NEDg | Description generation | batch_69b5b870a66c8190a59bfc0e99234596 |
completed | March 14, 2026, 7:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5b908fad88190846278c782a10cdb |
completed | March 14, 2026, 7:37 p.m. |
Created at: March 12, 2026, 11:07 p.m.