Triple
T12631943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | High Plains Drifter |
E301664
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Stefan Gierasch
Stefan Gierasch was an American character actor known for his numerous supporting roles in film and television from the 1950s through the 1990s.
|
E1019247
|
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: Stefan Gierasch | Statement: [High Plains Drifter, starring, Stefan Gierasch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stefan Gierasch Context triple: [High Plains Drifter, starring, Stefan Gierasch]
-
A.
Stefan Rowecki
Stefan Rowecki was a Polish general and key leader of the World War II resistance movement, serving as commander of the underground Home Army against Nazi occupation.
-
B.
Stefan Metzger
Stefan Metzger is a notable individual recognized as a prominent bearer of the Metzger surname.
-
C.
Stefan Grube
Stefan Grube is a film editor best known for his work on the thriller "10 Cloverfield Lane."
-
D.
Stefan Grube
Stefan Grube is an editor known for his work on the film "Tully."
-
E.
Dominik Grewe
Dominik Grewe is a computer scientist and researcher known for his contributions to deep reinforcement learning and AI systems, including work on AlphaGo Zero.
- 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: Stefan Gierasch Triple: [High Plains Drifter, starring, Stefan Gierasch]
Generated description
Stefan Gierasch was an American character actor known for his numerous supporting roles in film and television from the 1950s through the 1990s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stefan Gierasch Target entity description: Stefan Gierasch was an American character actor known for his numerous supporting roles in film and television from the 1950s through the 1990s.
-
A.
Stefan Rowecki
Stefan Rowecki was a Polish general and key leader of the World War II resistance movement, serving as commander of the underground Home Army against Nazi occupation.
-
B.
Stefan Metzger
Stefan Metzger is a notable individual recognized as a prominent bearer of the Metzger surname.
-
C.
Stefan Grube
Stefan Grube is a film editor best known for his work on the thriller "10 Cloverfield Lane."
-
D.
Stefan Grube
Stefan Grube is an editor known for his work on the film "Tully."
-
E.
Dominik Grewe
Dominik Grewe is a computer scientist and researcher known for his contributions to deep reinforcement learning and AI systems, including work on AlphaGo Zero.
- 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_69d7bdec9f9c8190b4bac675b7588211 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9610e4f408190946f37325d69375c |
completed | April 10, 2026, 8:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6d5ea02e08190b3be1fdfe86b4ee5 |
completed | May 3, 2026, 4:58 a.m. |
| NEDg | Description generation | batch_69f6d6e326408190b7906c7ea8e3ef85 |
completed | May 3, 2026, 5:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6d873b978819097962c82e8ffdac8 |
completed | May 3, 2026, 5:09 a.m. |
Created at: April 9, 2026, 5:15 p.m.