Triple
T35709268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Théâtre Optique |
E1031807
|
entity |
| Predicate | imageCarrierMaterial |
P142671
|
FINISHED |
| Object | gelatin or celluloid-based flexible strips |
—
|
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: gelatin or celluloid-based flexible strips | Statement: [Théâtre Optique, imageCarrierMaterial, gelatin or celluloid-based flexible strips]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: imageCarrierMaterial Context triple: [Théâtre Optique, imageCarrierMaterial, gelatin or celluloid-based flexible strips]
-
A.
imprintedOn
Indicates that one entity has formed a strong, often early-life, attachment or bond to another entity, typically treating it as a primary reference or caregiver.
-
B.
physicalCardMaterial
Indicates the material substance from which a physical card is made.
-
C.
informationCarrierType
chosen
Indicates the medium or format through which information is physically or digitally carried or delivered.
-
D.
banknoteMaterial
Indicates the material or substance from which a banknote is made.
-
E.
imageMaterial
Indicates that one entity serves as the material or physical medium from which the image entity is composed or rendered.
- 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_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:05 p.m.