Triple
T32460073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | African American women |
E829544
|
entity |
| Predicate | hasReligiousAffiliationTrend |
P76216
|
FINISHED |
| Object | Protestant Christianity |
E7436
|
NE 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: Protestant Christianity | Statement: [African American women, hasReligiousAffiliationTrend, Protestant Christianity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousAffiliationTrend Context triple: [African American women, hasReligiousAffiliationTrend, Protestant Christianity]
-
A.
religiousTrend
Indicates a pattern or direction of change over time in religious beliefs, practices, or affiliations among entities.
-
B.
religiousDemographyChange
chosen
Indicates a change over time in the religious composition or affiliation distribution within a population or region.
-
C.
hasReligious
Indicates that an entity is associated with, practices, or adheres to a particular religion or religious affiliation.
-
D.
religiousAffiliation
Indicates that one entity has a specified religious association, belief system, or denominational membership.
-
E.
religiousAffiliationLater
Indicates that an entity’s religious affiliation at a later time is the specified religion or organization.
- F. None of above.
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_69f3491df9288190afc0b23b1d6e72ce |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a0249374a8c8190ab19002a123da439 |
completed | May 11, 2026, 9:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3466914bf88190855c9e782c04ffe9 |
completed | June 18, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_6a02486194b08190a489ae3a8f4a59a9 |
completed | May 11, 2026, 9:21 p.m. |
Created at: May 1, 2026, 12:57 a.m.