Triple
T7907006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scientology |
E183600
|
entity |
| Predicate | hasLegalHistory |
P20840
|
FINISHED |
| Object | involved in numerous court cases worldwide |
—
|
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: involved in numerous court cases worldwide | Statement: [Scientology, hasLegalHistory, involved in numerous court cases worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegalHistory Context triple: [Scientology, hasLegalHistory, involved in numerous court cases worldwide]
-
A.
legalHistory
chosen
Indicates that there exists a record of past legal actions, cases, or statuses associated with an entity.
-
B.
hasHistoryOf
Indicates that an entity has a documented prior occurrence or background of a specified condition, event, or state.
-
C.
hasRegulationHistory
Indicates that there exists a record or sequence of regulatory actions, decisions, or statuses associated with the entity over time.
-
D.
hasLegalStatus
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
-
E.
hasLegalStatusInHistoriography
Indicates that an entity holds a particular recognized legal status or classification within historical or historiographical accounts of law and legal systems.
- 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_69ca828dec0c81908b8f55a4dbbb53ff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a5871b8819087ad69c116c40091 |
completed | March 31, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69cae92f9498819085277879e59aa072 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:03 p.m.