Triple
T3457177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen Mary (The King’s Speech) |
E72931
|
entity |
| Predicate | timeInStory |
P11197
|
FINISHED |
| Object | reign of King George V |
—
|
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: reign of King George V | Statement: [Queen Mary (The King’s Speech), timeInStory, reign of King George V]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeInStory Context triple: [Queen Mary (The King’s Speech), timeInStory, reign of King George V]
-
A.
timeOfNarrative
chosen
Indicates the specific time or period during which the events of a narrative are set or unfold.
-
B.
timeInMyth
Indicates that an entity exists or occurs during a specific time period within a mythological narrative or tradition.
-
C.
narrativeTimeSpanHours
Indicates the duration of a narrative or story event measured in hours.
-
D.
storyTimeSpanInFilm
Indicates the duration of time that the story or narrative covers within the film.
-
E.
spentTimeIn
Indicates that an entity has spent a certain amount or period of time in a particular place or context.
- 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_69ad85b12a908190a1d10a6b03b4f8ae |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbaa9837c8190aafd618c6af3446e |
completed | March 8, 2026, 6:06 p.m. |
| PD | Predicate disambiguation | batch_69adae041d588190a84a02bca94adec8 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:16 p.m.