Triple
T32373574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anne Goupil |
E827212
|
entity |
| Predicate | temporalSettingOfStory |
P11197
|
FINISHED |
| Object | late 1950s Paris |
—
|
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: late 1950s Paris | Statement: [Anne Goupil, temporalSettingOfStory, late 1950s Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: temporalSettingOfStory Context triple: [Anne Goupil, temporalSettingOfStory, late 1950s Paris]
-
A.
timeOfNarrative
chosen
Indicates the specific time or period during which the events of a narrative are set or unfold.
-
B.
storyTakesPlaceOver
Indicates that a story unfolds across or spans a specified duration of time.
-
C.
timeTravelExperimentDateInStory
Indicates the date on which a time travel experiment occurs within the narrative timeline of the story.
-
D.
placeOfSetting
Indicates the location or environment where an event, scene, or situation takes place.
-
E.
laterSettingOfFiction
Indicates that one fictional work is set chronologically later than another within a shared narrative or story world.
- 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_69f349177ddc8190ab0583f05597056b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc5740fc81909774a4f65201a3ff |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 12:50 a.m.