Triple
T9428246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Utopia |
E227307
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Claimstaker
Claimstaker is a component or sub-project of the Utopia system, likely focused on managing or asserting claims within that broader framework.
|
E800065
|
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: Claimstaker | Statement: [Utopia, hasPart, Claimstaker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Claimstaker Context triple: [Utopia, hasPart, Claimstaker]
-
A.
The Adjuster
"The Adjuster" is a short story by F. Scott Fitzgerald that explores themes of disillusionment, marital strain, and the emotional costs of modern life.
-
B.
Clearinghouse
Clearinghouse is a U.S. federal database that tracks commercial drivers’ drug and alcohol program violations to improve roadway safety and compliance.
-
C.
The Klaw
The Klaw is the nickname of NBA star Kawhi Leonard, renowned for his elite defense, massive hands, and calm, methodical playing style.
-
D.
The Litigators
The Litigators is a legal thriller novel by John Grisham that follows a small, struggling law firm drawn into a high-stakes mass tort lawsuit.
-
E.
The Kaseya
The Kaseya is the commonly used nickname for Kaseya Center, a major indoor sports and entertainment arena in Miami, Florida.
- 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: Claimstaker Triple: [Utopia, hasPart, Claimstaker]
Generated description
Claimstaker is a component or sub-project of the Utopia system, likely focused on managing or asserting claims within that broader framework.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Claimstaker Target entity description: Claimstaker is a component or sub-project of the Utopia system, likely focused on managing or asserting claims within that broader framework.
-
A.
The Adjuster
"The Adjuster" is a short story by F. Scott Fitzgerald that explores themes of disillusionment, marital strain, and the emotional costs of modern life.
-
B.
Clearinghouse
Clearinghouse is a U.S. federal database that tracks commercial drivers’ drug and alcohol program violations to improve roadway safety and compliance.
-
C.
The Klaw
The Klaw is the nickname of NBA star Kawhi Leonard, renowned for his elite defense, massive hands, and calm, methodical playing style.
-
D.
The Litigators
The Litigators is a legal thriller novel by John Grisham that follows a small, struggling law firm drawn into a high-stakes mass tort lawsuit.
-
E.
The Kaseya
The Kaseya is the commonly used nickname for Kaseya Center, a major indoor sports and entertainment arena in Miami, Florida.
- 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_69ca8436ba308190903e470776d2d893 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd7c92ee848190baa41fe91a131305 |
completed | April 1, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d11034369c81908992e268e66d7833 |
completed | April 4, 2026, 1:20 p.m. |
| NEDg | Description generation | batch_69d1149f6f6c81908ea2fce6f29ccb64 |
completed | April 4, 2026, 1:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d115168d748190909687d39fb79e24 |
completed | April 4, 2026, 1:41 p.m. |
Created at: March 30, 2026, 7:49 p.m.