Triple
T37355260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iron Chef |
E927435
|
entity |
| Predicate | hasInternationalAdaptations |
P203018
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Iron Chef, hasInternationalAdaptations, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInternationalAdaptations Context triple: [Iron Chef, hasInternationalAdaptations, yes]
-
A.
hasAdaptationsIn
Indicates that something possesses or exhibits adaptations within a particular context, environment, or domain.
-
B.
hasAdaptationsOfWorksIn
Indicates that an entity includes or contains adaptations of works that originate from another specified entity or context.
-
C.
adaptedInLanguage
Indicates that a work or content has been modified or translated so it can be presented or understood in a specified language.
-
D.
hasNotableAdaptationBy
Indicates that an original work has a significant adaptation created by the specified adapting entity (such as a person, group, or organization).
-
E.
languageOfMostAdaptations
Indicates the language in which the greatest number of adaptations of a given work or entity have been produced.
- 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_69f76eb701788190b40824bc4594d985 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a00dc330b148190aaae2ac6a5327960 |
completed | May 10, 2026, 7:27 p.m. |
| PD | Predicate disambiguation | batch_6a00d9d2904881909dafbfe7b9e5ad81 |
completed | May 10, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_6a00dc3268248190a723e1b7b29f9cda |
completed | May 10, 2026, 7:27 p.m. |
Created at: May 3, 2026, 4:16 p.m.