Triple
T18900699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joos |
E462331
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Peter Joos
Peter Joos is an individual notable enough to be recognized as a prominent bearer of the surname Joos.
|
E1348005
|
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: Peter Joos | Statement: [Joos, hasNotableBearer, Peter Joos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Joos Context triple: [Joos, hasNotableBearer, Peter Joos]
-
A.
Peter Wennink
Peter Wennink is a Dutch businessman best known for leading ASML, the world’s largest supplier of photolithography systems to the semiconductor industry, through a period of major global growth and technological advancement.
-
B.
Peter Roeck
Peter Roeck is a film editor known for his work on the movie "The Take."
-
C.
Peter Simonischek
Peter Simonischek was an acclaimed Austrian actor best known internationally for his lead role in the film "Toni Erdmann" and for his extensive work in European theater and cinema.
-
D.
Peter van Dam
Peter van Dam is a notable individual whose surname "van Dam" is recognized as being borne by him.
-
E.
Peter deVroede
Peter deVroede is a technology entrepreneur best known as a founder of the podcast platform Stitcher.
- 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: Peter Joos Triple: [Joos, hasNotableBearer, Peter Joos]
Generated description
Peter Joos is an individual notable enough to be recognized as a prominent bearer of the surname Joos.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Peter Joos Target entity description: Peter Joos is an individual notable enough to be recognized as a prominent bearer of the surname Joos.
-
A.
Peter Wennink
Peter Wennink is a Dutch businessman best known for leading ASML, the world’s largest supplier of photolithography systems to the semiconductor industry, through a period of major global growth and technological advancement.
-
B.
Peter Roeck
Peter Roeck is a film editor known for his work on the movie "The Take."
-
C.
Peter Simonischek
Peter Simonischek was an acclaimed Austrian actor best known internationally for his lead role in the film "Toni Erdmann" and for his extensive work in European theater and cinema.
-
D.
Peter van Dam
Peter van Dam is a notable individual whose surname "van Dam" is recognized as being borne by him.
-
E.
Peter deVroede
Peter deVroede is a technology entrepreneur best known as a founder of the podcast platform Stitcher.
- 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_69d8dcfd05bc819088903cca13cc2846 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c5289ba48190a6825c4db2e5e48d |
completed | April 20, 2026, 6:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0582bc878c8190bfb5f058aa272225 |
completed | May 14, 2026, 8:07 a.m. |
| NEDg | Description generation | batch_6a05871baa5881908c3c0f407b2d82c0 |
completed | May 14, 2026, 8:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0587acbf1c819088bae20aa89783eb |
completed | May 14, 2026, 8:28 a.m. |
Created at: April 10, 2026, 11:58 a.m.