Triple
T37717346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Timely Comics |
E939491
|
entity |
| Predicate | settingOfManyStories |
P195027
|
FINISHED |
| Object | World War II |
—
|
NE NERFINISHED |
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: World War II | Statement: [Timely Comics, settingOfManyStories, World War II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfManyStories Context triple: [Timely Comics, settingOfManyStories, World War II]
-
A.
settingOfMyth
Indicates that a location or environment serves as the backdrop or context in which a particular myth takes place.
-
B.
settingOfFrameStory
Indicates that one entity serves as the narrative setting or contextual backdrop within which the frame story of another entity takes place.
-
C.
mainSettingOfStory
Indicates that a location or environment serves as the primary setting in which the events of a story take place.
-
D.
settingInPlot
Indicates that a particular setting or location serves as the backdrop or environment in which the events of a plot take place.
-
E.
settingOfNarration
Indicates the place, time, or context in which a narrated event or story takes place.
- 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_69f76edc208c8190bc8b9683f75e1024 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd974d75e08190af46b1d608769f3b |
completed | May 8, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69fd94ff792c8190bedf4a639d3da809 |
completed | May 8, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69fd974c0e8481909fdd312897c647b3 |
completed | May 8, 2026, 7:57 a.m. |
Created at: May 3, 2026, 4:18 p.m.