Triple
T27057705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerald McBoing-Boing |
E684943
|
entity |
| Predicate | laterAdaptationFormat |
P97029
|
FINISHED |
| Object | television series |
—
|
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 series | Statement: [Gerald McBoing-Boing, laterAdaptationFormat, television series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterAdaptationFormat Context triple: [Gerald McBoing-Boing, laterAdaptationFormat, television series]
-
A.
laterAdaptedFor
Indicates that something was subsequently modified or repurposed to serve a new use, context, or medium.
-
B.
laterAdaptationName
Indicates that the object is the name of a later adaptation derived from or based on the subject.
-
C.
laterAdaptedIn
Indicates that something was subsequently adapted, modified, or reworked in a later context, version, or medium.
-
D.
laterMediaFormat
chosen
Indicates that one media format is a subsequent or updated version of another media format in time.
-
E.
filmAdaptationFormat
Indicates the specific medium or format (e.g., feature film, TV movie, short film) in which a work has been adapted into a film.
- 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_69ef14829fac8190914bef9ecc3005d7 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf769338819092a5f42653dcc956 |
completed | May 3, 2026, 10:43 p.m. |
Created at: April 27, 2026, 8:19 a.m.