Triple
T8486139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trash |
E200835
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object |
Gabriel Weinstein
Gabriel Weinstein is an actor best known for playing the character Trash.
|
E736151
|
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: Gabriel Weinstein | Statement: [Trash, portrayedBy, Gabriel Weinstein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gabriel Weinstein Context triple: [Trash, portrayedBy, Gabriel Weinstein]
-
A.
Gabriel Brener
Gabriel Brener is a businessman and investor best known in sports for his former ownership stake in Major League Soccer’s Houston Dynamo.
-
B.
Uriel Frisch
Uriel Frisch is a French physicist and mathematician renowned for his contributions to fluid dynamics and turbulence theory.
-
C.
Andrew Mondshein
Andrew Mondshein is an American film editor known for his work on acclaimed movies such as "Ma Rainey's Black Bottom" and "The Sixth Sense."
-
D.
Gabriel Weinberg
Gabriel Weinberg is an American entrepreneur and software engineer best known as the founder and CEO of the privacy-focused search engine DuckDuckGo.
-
E.
Ethan Gross
Ethan Gross is a screenwriter and producer best known for co-writing the science fiction film "Ad Astra" and his work on the television series "Fringe."
- 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: Gabriel Weinstein Triple: [Trash, portrayedBy, Gabriel Weinstein]
Generated description
Gabriel Weinstein is an actor best known for playing the character Trash.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gabriel Weinstein Target entity description: Gabriel Weinstein is an actor best known for playing the character Trash.
-
A.
Gabriel Brener
Gabriel Brener is a businessman and investor best known in sports for his former ownership stake in Major League Soccer’s Houston Dynamo.
-
B.
Uriel Frisch
Uriel Frisch is a French physicist and mathematician renowned for his contributions to fluid dynamics and turbulence theory.
-
C.
Andrew Mondshein
Andrew Mondshein is an American film editor known for his work on acclaimed movies such as "Ma Rainey's Black Bottom" and "The Sixth Sense."
-
D.
Gabriel Weinberg
Gabriel Weinberg is an American entrepreneur and software engineer best known as the founder and CEO of the privacy-focused search engine DuckDuckGo.
-
E.
Ethan Gross
Ethan Gross is a screenwriter and producer best known for co-writing the science fiction film "Ad Astra" and his work on the television series "Fringe."
- 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_69ca831d7b148190a6e32c1de43ab13b |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe53c4d608190a766c0e919a4b96f |
completed | March 31, 2026, 3:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce3a45e30c8190838ac499bbc66fbd |
completed | April 2, 2026, 9:43 a.m. |
| NEDg | Description generation | batch_69ce3c22f3c0819084803630d438c55e |
completed | April 2, 2026, 9:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce3ca57ec081909a14d962eee2c9a5 |
completed | April 2, 2026, 9:53 a.m. |
Created at: March 30, 2026, 6:12 p.m.