Triple
T11129965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ESV Women’s Study Bible |
E263249
|
entity |
| Predicate | audienceAge |
P10804
|
FINISHED |
| Object | adult |
—
|
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: adult | Statement: [ESV Women’s Study Bible, audienceAge, adult]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: audienceAge Context triple: [ESV Women’s Study Bible, audienceAge, adult]
-
A.
typicalAudience
chosen
Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
-
B.
audienceComposition
Indicates the makeup or distribution of different groups or segments within an audience in relation to something.
-
C.
primarySpeakersAgeGroup
Indicates the age range category to which the main or primary speakers in a context belong.
-
D.
audienceScale
Indicates the relative size or reach of the audience associated with an entity, event, or communication.
-
E.
relatesToAudience
Indicates a general relationship or relevance between something and a particular audience or group of recipients.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e831f4808190afabdaa0e97bbe32 |
completed | April 9, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69d7441efe948190ae4ab020121e169d |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:28 p.m.