Triple
T24829265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nancy Blansky |
E621285
|
entity |
| Predicate | portrayedInEra |
P116916
|
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: [Nancy Blansky, portrayedInEra, 1970s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedInEra Context triple: [Nancy Blansky, portrayedInEra, 1970s]
-
A.
depictedPersonEra
chosen
Indicates the historical era or time period associated with the person depicted in an image or representation.
-
B.
associatedProductionEra
Indicates a relationship where something is linked to the specific time period or era during which it was produced or created.
-
C.
livedInEra
Indicates that an entity existed or was active during a particular historical era or time period.
-
D.
appearsInFranchiseEra
Indicates that an entity (such as a work, character, or element) is part of or occurs within a specific era or phase of a larger franchise.
-
E.
appearsInTimePeriodDepicted
Indicates that something is present or occurs within the specific time period that is depicted or represented.
- 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_69e2fac0c3b881909110e5a56c6fa46f |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f43043512481909501a3979cac9947 |
completed | May 1, 2026, 4:46 a.m. |
| PD | Predicate disambiguation | batch_69f420fd375c81908ea4a4e60b76ee8f |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 5:09 a.m.