Triple
T16815272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheri Steinkellner |
E408727
|
entity |
| Predicate | hasRelative |
P367
|
FINISHED |
| Object |
Kit Steinkellner
Kit Steinkellner is an American television writer and playwright best known as the creator and showrunner of the drama series "Sorry for Your Loss."
|
E1234958
|
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: Kit Steinkellner | Statement: [Cheri Steinkellner, hasRelative, Kit Steinkellner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kit Steinkellner Context triple: [Cheri Steinkellner, hasRelative, Kit Steinkellner]
-
A.
Markus Sattler
Markus Sattler is a German software engineer and entrepreneur best known as a co-founder and former CTO of the email marketing platform Mailjet.
-
B.
Stephan Sauer
Stephan Sauer is a notable individual who shares the surname Sauer and is recognized for achievements significant enough to be specifically referenced.
-
C.
Stefan Vogl
Stefan Vogl is an ice hockey player known for emerging from the development system of the German club ESV Kaufbeuren.
-
D.
Stefan Grube
Stefan Grube is a film editor best known for his work on the thriller "10 Cloverfield Lane."
-
E.
Stefan Grube
Stefan Grube is an editor known for his work on the film "Tully."
- 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: Kit Steinkellner Triple: [Cheri Steinkellner, hasRelative, Kit Steinkellner]
Generated description
Kit Steinkellner is an American television writer and playwright best known as the creator and showrunner of the drama series "Sorry for Your Loss."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kit Steinkellner Target entity description: Kit Steinkellner is an American television writer and playwright best known as the creator and showrunner of the drama series "Sorry for Your Loss."
-
A.
Markus Sattler
Markus Sattler is a German software engineer and entrepreneur best known as a co-founder and former CTO of the email marketing platform Mailjet.
-
B.
Stephan Sauer
Stephan Sauer is a notable individual who shares the surname Sauer and is recognized for achievements significant enough to be specifically referenced.
-
C.
Stefan Vogl
Stefan Vogl is an ice hockey player known for emerging from the development system of the German club ESV Kaufbeuren.
-
D.
Stefan Grube
Stefan Grube is a film editor best known for his work on the thriller "10 Cloverfield Lane."
-
E.
Stefan Grube
Stefan Grube is an editor known for his work on the film "Tully."
- 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_69d88394566c8190b3dcbdc72935f7fa |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b2e0e05081908bd5eaa64abe133d |
completed | April 18, 2026, 4:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b2946ddc81908b1e7c662dc943ff |
completed | May 10, 2026, 4:30 p.m. |
| NEDg | Description generation | batch_6a00b3aafac08190b3e0181780f45392 |
completed | May 10, 2026, 4:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00b466ecd08190b7b5ee54476631ab |
completed | May 10, 2026, 4:37 p.m. |
Created at: April 10, 2026, 5:23 a.m.