Triple
T36266596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victory Project simulation apparatus |
E892241
|
entity |
| Predicate | simulatedSetting |
P54861
|
FINISHED |
| Object | 1950s-style utopian town of Victory |
—
|
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: 1950s-style utopian town of Victory | Statement: [Victory Project simulation apparatus, simulatedSetting, 1950s-style utopian town of Victory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: simulatedSetting Context triple: [Victory Project simulation apparatus, simulatedSetting, 1950s-style utopian town of Victory]
-
A.
usesRealisticSetting
Indicates that an event, narrative, or representation takes place within a setting that closely resembles real-world environments, conditions, or contexts.
-
B.
portrayedInSetting
chosen
Indicates that an entity is depicted or represented within a particular setting, environment, or context.
-
C.
indicatedSetting
Indicates that one entity specifies, denotes, or points out a particular setting or configuration associated with another entity.
-
D.
setting
Indicates the place, time, or context in which an event, action, or interaction occurs.
-
E.
revisedSetting
Indicates that an existing setting or configuration has been modified or updated from its previous state.
- 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_69f76e4699188190af045b11a840ce31 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b62749848190a5c9cedfae0eb7d4 |
completed | May 3, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c44390819084fb5558b354658f |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:09 p.m.