Triple
T10355005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Save the Tiger |
E243977
|
entity |
| Predicate | writtenInForm |
P93834
|
FINISHED |
| Object | screenplay adapted from novel |
—
|
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: screenplay adapted from novel | Statement: [Save the Tiger, writtenInForm, screenplay adapted from novel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writtenInForm Context triple: [Save the Tiger, writtenInForm, screenplay adapted from novel]
-
A.
wroteInForm
Indicates that an entity created or authored something using a specific format, style, or structural form.
-
B.
writtenForm
Indicates that one entity is the textual or orthographic representation (spelling or written version) of another entity.
-
C.
writingForm
Indicates the specific script, notation, or written representation used to express a piece of language or content.
-
D.
hasWrittenForm
Indicates that an entity is associated with a specific written or textual representation.
-
E.
writtenIn
Indicates that a work (such as a text, program, or document) is expressed or encoded using a particular language or notation.
- 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e953d4888190b7ca0ac932349dbf |
completed | April 7, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69d4dfa657f481909cc5cc8fec00ad19 |
completed | April 7, 2026, 10:42 a.m. |
| PDg | Predicate description generation | batch_69d4e91ce2008190af252c140370b7f2 |
completed | April 7, 2026, 11:23 a.m. |
Created at: April 6, 2026, 11:58 a.m.