Triple
T13343066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silent film |
E317871
|
entity |
| Predicate | usesTextElement |
P62426
|
FINISHED |
| Object | title cards |
—
|
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: title cards | Statement: [Silent film, usesTextElement, title cards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTextElement Context triple: [Silent film, usesTextElement, title cards]
-
A.
hasTextElement
chosen
Indicates that an entity contains or is associated with a specific text-based component or segment.
-
B.
usesTextService
Indicates that an entity makes use of a text-based service to perform some function or obtain some benefit.
-
C.
usesElement
Indicates that one entity makes use of, incorporates, or depends on a specified element in its structure, function, or behavior.
-
D.
hasText
Indicates that an entity is associated with or contains a specific piece of textual content.
-
E.
allowsText
Indicates that one entity permits or supports the use, input, or display of textual content in relation to 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e8839b48190b164414b418e756c |
completed | April 11, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69d98f6e53d88190bd6aa42f69b10ffb |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:31 p.m.