Triple
T37177099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarah Frances Croker-Poole |
E921081
|
entity |
| Predicate | religionAfterMarriage |
P194121
|
FINISHED |
| Object | Islam |
—
|
NE NERFINISHED |
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: Islam | Statement: [Sarah Frances Croker-Poole, religionAfterMarriage, Islam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religionAfterMarriage Context triple: [Sarah Frances Croker-Poole, religionAfterMarriage, Islam]
-
A.
religiousStatusAfterEvent
chosen
Indicates the religious status or affiliation an entity has as a result of a specified event or change.
-
B.
religiousStatus
Indicates the religious affiliation, role, or standing that an entity holds within a religious context.
-
C.
namedAfterReligion
Indicates that an entity’s name is derived from or inspired by a particular religion or religious tradition.
-
D.
religiousCondition
Indicates a condition, requirement, or circumstance that is defined or constrained by religious beliefs, practices, or affiliations.
-
E.
spouseReligiousTradition
Indicates that there is a relationship specifying the religious tradition or affiliation of a person's spouse.
- 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_69f76ea16f288190b445aa1604d996f4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a00144238708190acbec3f791cc873e |
completed | May 10, 2026, 5:14 a.m. |
| PD | Predicate disambiguation | batch_6a00120244a4819090ef39070aba9d99 |
completed | May 10, 2026, 5:05 a.m. |
Created at: May 3, 2026, 4:15 p.m.