Triple
T19753460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Republic of Gilead |
E474442
|
entity |
| Predicate | womenClassSystem |
P11611
|
FINISHED |
| Object | Handmaids |
—
|
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: Handmaids | Statement: [Republic of Gilead, womenClassSystem, Handmaids]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: womenClassSystem Context triple: [Republic of Gilead, womenClassSystem, Handmaids]
-
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.
hasGenderSystem
chosen
Indicates that an entity employs or is characterized by a particular system for categorizing gender.
-
D.
femaleBranch
Indicates that one entity is a female branch or female-line subdivision of another entity within a hierarchical or genealogical structure.
-
E.
womenTraining
Indicates that one or more women are engaged in a training activity or process.
- 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6529cae048190b4f8e6ba409bcf8e |
completed | April 20, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69e5305016e08190b9561a96baecb0b8 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:48 p.m.