Triple
T5008099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Commander Judd |
E112545
|
entity |
| Predicate | themeContext |
P56597
|
FINISHED |
| Object | patriarchy |
—
|
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: patriarchy | Statement: [Commander Judd, themeContext, patriarchy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: themeContext Context triple: [Commander Judd, themeContext, patriarchy]
-
A.
themeFor
Indicates that something serves as the central subject, topic, or focus for another thing (such as an event, work, or activity).
-
B.
centralThemeContext
chosen
Indicates that one concept serves as the main thematic focus within the situational, narrative, or discourse context defined by another.
-
C.
theme
Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
-
D.
themeContrast
Indicates a relationship where two themes are compared or opposed to highlight their differences or tension.
-
E.
themeExamples
Indicates that the related entity serves as an example or illustration of the theme expressed by the subject.
- 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_69bd4433d0b08190877e83959ef40d81 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd730a7590819088ab8d49c5c88c2f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd714cbc448190aa53a8a83d768b64 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:35 p.m.