Triple
T16815279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheri Steinkellner |
E408727
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object |
Teddy Steinkellner
Teddy Steinkellner is an American writer and producer, known for his work in television and young adult fiction.
|
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: Teddy Steinkellner | Statement: [Cheri Steinkellner, hasChild, Teddy Steinkellner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teddy Steinkellner Context triple: [Cheri Steinkellner, hasChild, Teddy Steinkellner]
-
A.
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."
-
B.
Stefan Grube
Stefan Grube is a film editor best known for his work on the thriller "10 Cloverfield Lane."
-
C.
Stefan Grube
Stefan Grube is an editor known for his work on the film "Tully."
-
D.
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.
-
E.
Stefan Vogl
Stefan Vogl is an ice hockey player known for emerging from the development system of the German club ESV Kaufbeuren.
- 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: Teddy Steinkellner Triple: [Cheri Steinkellner, hasChild, Teddy Steinkellner]
Generated description
Teddy Steinkellner is an American writer and producer, known for his work in television and young adult fiction.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Teddy Steinkellner Target entity description: Teddy Steinkellner is an American writer and producer, known for his work in television and young adult fiction.
-
A.
Kit Steinkellner
chosen
Kit Steinkellner is an American television writer and playwright best known as the creator and showrunner of the drama series "Sorry for Your Loss."
-
B.
Stefan Grube
Stefan Grube is a film editor best known for his work on the thriller "10 Cloverfield Lane."
-
C.
Stefan Grube
Stefan Grube is an editor known for his work on the film "Tully."
-
D.
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.
-
E.
Stefan Vogl
Stefan Vogl is an ice hockey player known for emerging from the development system of the German club ESV Kaufbeuren.
- F. None of above.
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_6a00c29ea9fc81909087cdf28c9c9fc0 |
completed | May 10, 2026, 5:38 p.m. |
| NEDg | Description generation | batch_6a00c345229481909d8c0b8a122266bb |
completed | May 10, 2026, 5:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00c42315448190aecedc58fa0b7319 |
completed | May 10, 2026, 5:45 p.m. |
Created at: April 10, 2026, 5:23 a.m.