Triple
T14966979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mitchell v. United States |
E373214
|
entity |
| Predicate | petitioner |
P3132
|
FINISHED |
| Object |
Amanda Mitchell
Amanda Mitchell is the named petitioner in the U.S. Supreme Court case Mitchell v. United States.
|
E1331665
|
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: Amanda Mitchell | Statement: [Mitchell v. United States, petitioner, Amanda Mitchell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amanda Mitchell Context triple: [Mitchell v. United States, petitioner, Amanda Mitchell]
-
A.
Amanda Robinson
Amanda Robinson is the spouse of Jason Robinson.
-
B.
Amanda Woods
Amanda Woods is a successful but emotionally guarded Los Angeles movie trailer producer who swaps homes with a British woman over Christmas in the romantic comedy film "The Holiday."
-
C.
Amanda Thompson
Amanda Thompson is a prominent member of the Thompson family, known for her public profile and contributions that have brought recognition to the family name.
-
D.
Amanda Kelly
Amanda Kelly is a technology entrepreneur best known as a co-founder of Streamlit, an open-source framework for building data and machine learning web apps in Python.
-
E.
Amanda Naughton
Amanda Naughton is an American actress best known for her starring role on the 1990s television series "Remember WENN."
- 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: Amanda Mitchell Triple: [Mitchell v. United States, petitioner, Amanda Mitchell]
Generated description
Amanda Mitchell is the named petitioner in the U.S. Supreme Court case Mitchell v. United States.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Amanda Mitchell Target entity description: Amanda Mitchell is the named petitioner in the U.S. Supreme Court case Mitchell v. United States.
-
A.
Amanda Robinson
Amanda Robinson is the spouse of Jason Robinson.
-
B.
Amanda Woods
Amanda Woods is a successful but emotionally guarded Los Angeles movie trailer producer who swaps homes with a British woman over Christmas in the romantic comedy film "The Holiday."
-
C.
Amanda Thompson
Amanda Thompson is a prominent member of the Thompson family, known for her public profile and contributions that have brought recognition to the family name.
-
D.
Amanda Kelly
Amanda Kelly is a technology entrepreneur best known as a co-founder of Streamlit, an open-source framework for building data and machine learning web apps in Python.
-
E.
Amanda Naughton
Amanda Naughton is an American actress best known for her starring role on the 1990s television series "Remember WENN."
- 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6e2fdcc8190bffe603db3388736 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a04f86dd054819084e9540deb2c836e |
completed | May 13, 2026, 10:17 p.m. |
| NEDg | Description generation | batch_6a04f9adb7e88190ab5cf82412fc4e11 |
completed | May 13, 2026, 10:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a04fa3fc8348190970145b3718cb01d |
completed | May 13, 2026, 10:25 p.m. |
Created at: April 10, 2026, 2:47 a.m.