Triple
T16994610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elena Hood |
E412281
|
entity |
| Predicate | decadeOfFictionalSetting |
P96395
|
FINISHED |
| Object | 1970s |
—
|
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: 1970s | Statement: [Elena Hood, decadeOfFictionalSetting, 1970s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: decadeOfFictionalSetting Context triple: [Elena Hood, decadeOfFictionalSetting, 1970s]
-
A.
storySettingDecade
chosen
Indicates the decade in which the events or setting of a story take place.
-
B.
filmSettingDecade
Indicates the decade in which the events or primary narrative of a film are set.
-
C.
fictionalEra
Indicates the time period or age within a fictional or imaginary setting in which an entity exists or an event occurs.
-
D.
fictionalCenturyOfOrigin
Indicates the fictional century in which an entity is depicted as having originated or first appeared within its narrative world.
-
E.
hasFictionalSettingElement
Indicates that something includes or is associated with a specific element or component of a fictional setting.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d285f35881908c32b2f27ba7f0ac |
completed | April 18, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69e35d552bc08190af17ef7659e094ef |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:32 a.m.