Triple
T75767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jehovah's Witnesses |
E1513
|
entity |
| Predicate | hasFaced |
P2189
|
FINISHED |
| Object | legal cases on religious freedom |
—
|
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: legal cases on religious freedom | Statement: [Jehovah's Witnesses, hasFaced, legal cases on religious freedom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFaced Context triple: [Jehovah's Witnesses, hasFaced, legal cases on religious freedom]
-
A.
hasSpokenAbout
Indicates that one entity has verbally expressed, discussed, or mentioned another entity or topic.
-
B.
hasChallenge
chosen
Indicates that an entity faces, experiences, or is confronted with a particular difficulty, obstacle, or problem.
-
C.
hasPerson
Indicates that an entity is associated with or includes a specific person.
-
D.
hasBeard
Indicates that one entity possesses or displays a beard.
-
E.
hasReception
Indicates that an entity hosts, includes, or is associated with a reception event (such as a formal gathering or welcoming function).
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a25314bd6c81908d1cfd4b83f20049 |
completed | Feb. 28, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_69a24eae77ec81909015906f31f2b62e |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.