Triple
T13473258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angelique Bouchard |
E318182
|
entity |
| Predicate | turnsInto |
P65473
|
FINISHED |
| Object | vampire creator of Barnabas Collins (2012 film) |
—
|
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: vampire creator of Barnabas Collins (2012 film) | Statement: [Angelique Bouchard, turnsInto, vampire creator of Barnabas Collins (2012 film)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turnsInto Context triple: [Angelique Bouchard, turnsInto, vampire creator of Barnabas Collins (2012 film)]
-
A.
turns
Indicates a change in orientation, direction, or state initiated by one entity affecting itself or another entity.
-
B.
bodyTransformedInto
chosen
Indicates that one entity’s physical form is changed or converted into another specified form or entity.
-
C.
turnsIn
Indicates that an entity submits or hands over something, typically work or an item, to another party or authority.
-
D.
emergesAs
Indicates that one entity comes to be recognized, develops, or appears in the role, form, or status of another entity over time.
-
E.
wasTransformedBy
Indicates that an entity has undergone a change of state, form, or condition as the result of an action, process, or agent.
- 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf2447bc81908baf1f4b55095144 |
completed | April 12, 2026, 2:41 p.m. |
| PD | Predicate disambiguation | batch_69dbadfddefc81909ef7fde23b181b5c |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:42 p.m.