Triple
T23128129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben Becker |
E577092
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object |
Monika Hansen
Monika Hansen was a German actress known for her work in film, television, and theater, and as a member of a prominent acting family.
|
E1575972
|
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: Monika Hansen | Statement: [Ben Becker, mother, Monika Hansen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monika Hansen Context triple: [Ben Becker, mother, Monika Hansen]
-
A.
Monika Henreid
Monika Henreid is the daughter of classic Hollywood actor and director Paul Henreid, known for his roles in films such as "Casablanca" and "Now, Voyager."
-
B.
Mona Jensen
Mona Jensen is the central protagonist of the Danish medical drama film "The Kingdom," around whom much of the story’s hospital-based mystery and tension revolves.
-
C.
Monika Willi
Monika Willi is an acclaimed Austrian film editor known for her work on numerous internationally recognized art-house and auteur films.
-
D.
Monika Thiel
Monika Thiel is a person notable enough to be recognized as a significant bearer of the surname Thiel.
-
E.
Jennifer Hansen
Jennifer Hansen is an Australian television news presenter and journalist, best known for her work with Network Ten.
- 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: Monika Hansen Triple: [Ben Becker, mother, Monika Hansen]
Generated description
Monika Hansen was a German actress known for her work in film, television, and theater, and as a member of a prominent acting family.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Monika Hansen Target entity description: Monika Hansen was a German actress known for her work in film, television, and theater, and as a member of a prominent acting family.
-
A.
Monika Henreid
Monika Henreid is the daughter of classic Hollywood actor and director Paul Henreid, known for his roles in films such as "Casablanca" and "Now, Voyager."
-
B.
Mona Jensen
Mona Jensen is the central protagonist of the Danish medical drama film "The Kingdom," around whom much of the story’s hospital-based mystery and tension revolves.
-
C.
Monika Willi
Monika Willi is an acclaimed Austrian film editor known for her work on numerous internationally recognized art-house and auteur films.
-
D.
Monika Thiel
Monika Thiel is a person notable enough to be recognized as a significant bearer of the surname Thiel.
-
E.
Jennifer Hansen
Jennifer Hansen is an Australian television news presenter and journalist, best known for her work with Network Ten.
- 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_69e245f7b0e481909c473ff4e6a54e2c |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18e857b40819081f9df03fff64d48 |
completed | April 29, 2026, 4:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c308583d481908c7a750fd7fba044 |
completed | May 19, 2026, 9:42 a.m. |
| NEDg | Description generation | batch_6a0c378c36cc8190b4470dceb62f99ad |
completed | May 19, 2026, 10:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c387daf6481909cd5f3cc19636575 |
completed | May 19, 2026, 10:16 a.m. |
Created at: April 17, 2026, 3:59 p.m.