Triple
T1770957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wonder Woman (2017 film) |
E38872
|
entity |
| Predicate | storyBy |
P1955
|
FINISHED |
| Object |
Jason Fuchs
Jason Fuchs is an American screenwriter and actor best known for writing major studio films such as Wonder Woman (2017) and Pan (2015).
|
E245535
|
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: Jason Fuchs | Statement: [Wonder Woman (2017 film), storyBy, Jason Fuchs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jason Fuchs Context triple: [Wonder Woman (2017 film), storyBy, Jason Fuchs]
-
A.
Eric Wetzels
Eric Wetzels is a Dutch politician who serves as the chairperson of the People's Party for Freedom and Democracy (VVD).
-
B.
Justin Elicker
Justin Elicker is an American politician who serves as the mayor of New Haven, Connecticut, known for his focus on urban development, education, and social equity.
-
C.
Jonathan Teplitzky
Jonathan Teplitzky is an Australian film director known for character-driven dramas such as "The Railway Man" and "Burning Man."
-
D.
Evan Schiff
Evan Schiff is a film editor known for his work on high-profile action movies, including entries in the John Wick franchise.
-
E.
Matthew Schmidt
Matthew Schmidt is a film editor best known for his work on major Marvel Cinematic Universe films, including Avengers: Infinity War.
- 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: Jason Fuchs Triple: [Wonder Woman (2017 film), storyBy, Jason Fuchs]
Generated description
Jason Fuchs is an American screenwriter and actor best known for writing major studio films such as Wonder Woman (2017) and Pan (2015).
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jason Fuchs Target entity description: Jason Fuchs is an American screenwriter and actor best known for writing major studio films such as Wonder Woman (2017) and Pan (2015).
-
A.
Eric Wetzels
Eric Wetzels is a Dutch politician who serves as the chairperson of the People's Party for Freedom and Democracy (VVD).
-
B.
Justin Elicker
Justin Elicker is an American politician who serves as the mayor of New Haven, Connecticut, known for his focus on urban development, education, and social equity.
-
C.
Jonathan Teplitzky
Jonathan Teplitzky is an Australian film director known for character-driven dramas such as "The Railway Man" and "Burning Man."
-
D.
Evan Schiff
Evan Schiff is a film editor known for his work on high-profile action movies, including entries in the John Wick franchise.
-
E.
Brian Schmetzer
Brian Schmetzer is an American soccer coach best known for leading Seattle Sounders FC to multiple MLS Cup titles and establishing the club as a perennial league contender.
- 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa648fe908819098fd27b74b17fabb |
completed | March 6, 2026, 5:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae651f8f38819089fb40e7bb3dc2cb |
completed | March 9, 2026, 6:13 a.m. |
| NEDg | Description generation | batch_69ae6615cf488190aa5bdf5431c8628a |
completed | March 9, 2026, 6:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae668ef8bc819085ed1c83f447d396 |
completed | March 9, 2026, 6:19 a.m. |
Created at: March 4, 2026, 7:31 p.m.