Triple
T37722038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fanny Herself |
E939609
|
entity |
| Predicate | protagonistReligionOrEthnicity |
P83945
|
FINISHED |
| Object | Jewish |
—
|
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: Jewish | Statement: [Fanny Herself, protagonistReligionOrEthnicity, Jewish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistReligionOrEthnicity Context triple: [Fanny Herself, protagonistReligionOrEthnicity, Jewish]
-
A.
religionOfCharacterPortrayed
chosen
Indicates that a work portrays a character as adhering to or being associated with a particular religion.
-
B.
portraysReligionAs
Indicates that one entity represents, depicts, or characterizes a religion in a particular way.
-
C.
hasReligiousCharacter
Indicates that an entity possesses a religious nature, function, or affiliation, or is characterized by religious aspects or significance.
-
D.
religiousCharacteristic
Indicates that one entity has a religious attribute, quality, or affiliation that characterizes or distinguishes it in a religious context.
-
E.
spokenByReligion
Indicates that something (such as a text, doctrine, or statement) is expressed or articulated by a particular religion or religious tradition.
- 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_69f76edc208c8190bc8b9683f75e1024 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaef0cec881908c2742d77d145901 |
completed | May 6, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69fbadf632ec8190b14991c971258307 |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:18 p.m.