Triple
T35604240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johanna Baker |
E1028839
|
entity |
| Predicate | portrayedInLanguageVersion |
P199715
|
FINISHED |
| Object | English-language version of The Big Blue |
—
|
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: English-language version of The Big Blue | Statement: [Johanna Baker, portrayedInLanguageVersion, English-language version of The Big Blue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedInLanguageVersion Context triple: [Johanna Baker, portrayedInLanguageVersion, English-language version of The Big Blue]
-
A.
presentedInLanguage
Indicates that something (such as content, information, or a work) is expressed or made available using a particular language.
-
B.
voicedInLanguage
Indicates that an entity produces spoken or vocal output using a specified language.
-
C.
playedInLanguage
Indicates that an audiovisual work was performed or produced in a specified language.
-
D.
portrayalLanguage
Indicates the language in which something is depicted, represented, or expressed.
-
E.
languageSpokenOnScreen
Indicates that a particular language is used in spoken dialogue or audible communication within an on-screen work (such as a film, show, or video).
- 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_69f76e0653ec81909b1b813c126c6574 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff519b65f081909902ba83b775ef85 |
completed | May 9, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69ff506fccdc8190bd93269589040aed |
completed | May 9, 2026, 3:19 p.m. |
| PDg | Predicate description generation | batch_69ff519a67008190b1eda931fdeff53e |
completed | May 9, 2026, 3:24 p.m. |
Created at: May 3, 2026, 4:05 p.m.