Triple
T9873872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | District Court of American Samoa |
E240024
|
entity |
| Predicate | hasCaseLoadType |
P4217
|
FINISHED |
| Object | high-volume local matters |
—
|
LITERAL FINISHED |
How this triple was built (2 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: high-volume local matters | Statement: [District Court of American Samoa, hasCaseLoadType, high-volume local matters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCaseLoadType Context triple: [District Court of American Samoa, hasCaseLoadType, high-volume local matters]
-
A.
hasTypeOfCase
chosen
Indicates that an entity is associated with or classified under a particular type or category of case.
-
B.
hasTypeOfCourt
Indicates that an entity is associated with or classified by a specific type or category of court.
-
C.
hasTaskType
Indicates that an entity is associated with or classified under a specific type or category of task.
-
D.
hasJudgeType
Indicates that an entity is associated with a specific category or type of judge.
-
E.
hasLegalSystemType
Indicates that an entity possesses or is governed by a particular type or form of legal system.
- F. None of above.
Provenance (3 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_69ca84e8a0788190b9061811d50fd554 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3f89fa081908b58956902c193cf |
completed | April 2, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69cd1d7621d48190aa6a6f34399514b0 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:37 p.m.