Triple
T37376231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anneliese Michel |
E927988
|
entity |
| Predicate | numberOfExorcismSessions |
P205872
|
FINISHED |
| Object | 67 |
—
|
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: 67 | Statement: [Anneliese Michel, numberOfExorcismSessions, 67]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfExorcismSessions Context triple: [Anneliese Michel, numberOfExorcismSessions, 67]
-
A.
exorcisedBy
Indicates that an entity has had a spirit, demon, or malign supernatural influence driven out or removed by another entity.
-
B.
apparitionWitnessCount
Indicates the number of distinct observers who witnessed a particular apparition event.
-
C.
numberOfExiles
Indicates the quantity of entities that have been exiled in the context of a given subject or situation.
-
D.
hasFormerExorcistCharacter
Indicates that a work includes at least one character who previously served as an exorcist but no longer does so.
-
E.
apparitionFrequency
Indicates how often an entity appears, manifests, or becomes perceptible within a given context or timeframe.
- 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_69f76eb820248190a5c395ca50ad002a |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a13a1308190a202df66f4781855 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:16 p.m.