Triple
T36266455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victory Project simulation |
E892237
|
entity |
| Predicate | physicalStateOfWomen |
P184825
|
FINISHED |
| Object | bodies kept in the real world while minds are in simulation |
—
|
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: bodies kept in the real world while minds are in simulation | Statement: [Victory Project simulation, physicalStateOfWomen, bodies kept in the real world while minds are in simulation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: physicalStateOfWomen Context triple: [Victory Project simulation, physicalStateOfWomen, bodies kept in the real world while minds are in simulation]
-
A.
womenStatus
Indicates the social, legal, economic, or cultural position or condition assigned to women within a given context or system.
-
B.
femaleMass
Indicates that the subject has a mass value specifically associated with its female form or female population.
-
C.
femaleSubject
Indicates that the subject in the relationship or action is female.
-
D.
femaleFeature
Indicates that the subject possesses a characteristic or attribute that is typically associated with females.
-
E.
femaleHas
Indicates that a specified entity is female or possesses a female gender attribute in relation to another entity or context.
- 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_69f76e4699188190af045b11a840ce31 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b6267e488190bbebcd8b4acc7e1b |
completed | May 3, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c44390819084fb5558b354658f |
completed | May 3, 2026, 8:49 p.m. |
| PDg | Predicate description generation | batch_69f7b57aa0848190a22c31c3ff90e0ab |
completed | May 3, 2026, 8:52 p.m. |
Created at: May 3, 2026, 4:09 p.m.