Triple
T5411408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel in the lions' den |
E121019
|
entity |
| Predicate | outcomeForAccusers |
P63287
|
FINISHED |
| Object | accusers are thrown into the lions' den |
—
|
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: accusers are thrown into the lions' den | Statement: [Daniel in the lions' den, outcomeForAccusers, accusers are thrown into the lions' den]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: outcomeForAccusers Context triple: [Daniel in the lions' den, outcomeForAccusers, accusers are thrown into the lions' den]
-
A.
hasAccuser
Indicates that one entity serves as the accuser of another entity in a dispute, complaint, or allegation.
-
B.
accuserIn
Indicates that one entity is the party who brings a charge or accusation against another entity within a specific context or case.
-
C.
accusedIn
Indicates that a person or entity is formally charged with wrongdoing in a particular case, proceeding, or context.
-
D.
numberOfPeopleAccused
Indicates the count of individuals who are formally alleged to have committed a particular act or offense.
-
E.
accusedGroup
Indicates that one group is formally charged or blamed by another party for committing a wrongdoing or offense.
- F. None of above. chosen
Provenance (4 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_69bd463a41cc8190b32ff5af2b96ca93 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd87b9e578819086380ff18a633cb0 |
completed | March 20, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69bd8467e6b48190b9eaa9de67072e06 |
completed | March 20, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69bd865702ec8190831bde2c2a331f28 |
completed | March 20, 2026, 5:39 p.m. |
Created at: March 20, 2026, 2:05 p.m.