Triple
T375574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ware v. Hylton |
E8364
|
entity |
| Predicate | plaintiff |
P660
|
FINISHED |
| Object |
Ware
Ware was the plaintiff in the landmark U.S. Supreme Court case Ware v. Hylton, which addressed the supremacy of federal treaties over conflicting state laws.
|
E47937
|
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: Ware | Statement: [Ware v. Hylton, plaintiff, Ware]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ware Context triple: [Ware v. Hylton, plaintiff, Ware]
-
A.
WD
WD is a consumer-facing brand of Western Digital known for its hard drives, solid-state drives, and other data storage products.
-
B.
EA
EA is the commonly used abbreviation for the Environment Agency, the public body responsible for environmental protection and regulation in England.
-
C.
Carrier
Carrier is a leading global brand specializing in heating, ventilation, air conditioning (HVAC), and refrigeration solutions.
-
D.
Opera Software
Opera Software is a Norwegian software company best known for developing the Opera web browser and related internet technologies.
-
E.
WAS
WAS is the standard three-letter abbreviation used for the NBA team Washington Wizards.
- 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: Ware Triple: [Ware v. Hylton, plaintiff, Ware]
Generated description
Ware was the plaintiff in the landmark U.S. Supreme Court case Ware v. Hylton, which addressed the supremacy of federal treaties over conflicting state laws.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ware Target entity description: Ware was the plaintiff in the landmark U.S. Supreme Court case Ware v. Hylton, which addressed the supremacy of federal treaties over conflicting state laws.
-
A.
WD
WD is a consumer-facing brand of Western Digital known for its hard drives, solid-state drives, and other data storage products.
-
B.
EA
EA is the commonly used abbreviation for the Environment Agency, the public body responsible for environmental protection and regulation in England.
-
C.
Carrier
Carrier is a leading global brand specializing in heating, ventilation, air conditioning (HVAC), and refrigeration solutions.
-
D.
Opera Software
Opera Software is a Norwegian software company best known for developing the Opera web browser and related internet technologies.
-
E.
WAS
WAS is the standard three-letter abbreviation used for the Washington Commanders NFL franchise.
- 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec1585648190943f1c698e9b2d81 |
completed | Feb. 28, 2026, 1:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3f4dbf49081908ccd464668483b77 |
completed | March 1, 2026, 8:12 a.m. |
| NEDg | Description generation | batch_69a3f6d18c488190ab509ded4d5b0367 |
completed | March 1, 2026, 8:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3fa368edc8190ac00be2189df7cf9 |
completed | March 1, 2026, 8:35 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.