Triple
T7851696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susan Bradley |
E182068
|
entity |
| Predicate | appearsInFilmLanguage |
P52200
|
FINISHED |
| Object | English |
—
|
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 | Statement: [Susan Bradley, appearsInFilmLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearsInFilmLanguage Context triple: [Susan Bradley, appearsInFilmLanguage, English]
-
A.
areSpokenIn
Indicates that a particular language is used as a spoken means of communication within a specified region, community, or context.
-
B.
languageSpokenOnScreen
chosen
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).
-
C.
hasLanguageInUniverse
Indicates that a particular language exists or is used within a specified fictional or conceptual universe.
-
D.
languageOfReleases
Indicates the language in which the releases associated with an entity are produced or published.
-
E.
languageOfPrimaryNarrations
Indicates the language in which the main or primary narrations are expressed or conveyed.
- 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_69ca82869ee08190b8f9040dbc2c0467 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb18ec48548190960bd564a60effa8 |
completed | March 31, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_69cae92180f88190ae3d44c3de7adc93 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:51 p.m.