Triple
T35709286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Théâtre Optique |
E1031807
|
entity |
| Predicate | imageRegistrationMethod |
P119941
|
FINISHED |
| Object | perforations or guides for alignment |
—
|
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: perforations or guides for alignment | Statement: [Théâtre Optique, imageRegistrationMethod, perforations or guides for alignment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: imageRegistrationMethod Context triple: [Théâtre Optique, imageRegistrationMethod, perforations or guides for alignment]
-
A.
reconstructionMethod
Indicates the technique or process used to reconstruct, restore, or rebuild something from its original or fragmented state.
-
B.
imagingActivation
Indicates that an entity initiates or undergoes an activation process related to imaging or image-based functionality.
-
C.
photoRecognition
Indicates that one entity identifies or verifies another entity based on information extracted from a photograph.
-
D.
alignmentMethod
chosen
Indicates the technique or procedure used to align one entity with another or with a reference standard.
-
E.
imagedIn
Indicates that one entity appears within or is depicted in an image associated with another entity.
- 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_69f76e0df1d08190965b1c6dff94c391 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d219f8819081dc4ce3c83ca0cb |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4:05 p.m.