Triple
T26976253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anu |
E679465
|
entity |
| Predicate | fictionalSettingTimePeriod |
P106751
|
FINISHED |
| Object | 1960s |
—
|
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: 1960s | Statement: [Anu, fictionalSettingTimePeriod, 1960s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalSettingTimePeriod Context triple: [Anu, fictionalSettingTimePeriod, 1960s]
-
A.
fictionalEra
Indicates the time period or age within a fictional or imaginary setting in which an entity exists or an event occurs.
-
B.
fictionalTime
Indicates that the associated time or temporal reference exists only within a fictional or imagined context, rather than in real-world chronology.
-
C.
fictionalAge
Indicates the age attributed to an entity within a fictional or narrative context, rather than its real-world age.
-
D.
fictionalTimeDepth
chosen
Indicates a relationship where an entity is associated with a time period or temporal depth that exists only within a fictional or imagined context.
-
E.
workOfFictionSetting
Indicates that a work of fiction is set in, or primarily takes place within, a particular location, time, or environment.
- 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_69eeeb507a7081909d516e1fa08b7d29 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f6b903538481909cffcb6cc1cc0e70 |
completed | May 3, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69f6b626120c819097c9ad04487570d7 |
completed | May 3, 2026, 2:42 a.m. |
Created at: April 27, 2026, 6:42 a.m.