Triple
T35955163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamran |
E1039835
|
entity |
| Predicate | featuredInAdaptationType |
P61944
|
FINISHED |
| Object | television adaptation |
—
|
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: television adaptation | Statement: [Kamran, featuredInAdaptationType, television adaptation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuredInAdaptationType Context triple: [Kamran, featuredInAdaptationType, television adaptation]
-
A.
adaptedAs
Indicates that one work, concept, or entity has been transformed or re-created into another form or medium based on the original.
-
B.
hasAdaptationsIn
Indicates that something possesses or exhibits adaptations within a particular context, environment, or domain.
-
C.
notableAdaptationType
Indicates that one work is a significant adaptation of another work in a specific way or medium (e.g., film adaptation, stage adaptation).
-
D.
adaptationIncludes
Indicates that an adaptation incorporates, contains, or makes use of a particular component, element, or feature as part of its adapted form.
-
E.
appearsInAdaptationBy
chosen
Indicates that an entity is featured or present in an adaptation created by a specified adapter (e.g., author, director, or studio).
- 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_69f76e25ea488190b7cee970b3e70382 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0895b48190acdd88dc10db7be7 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:07 p.m.