Triple
T38700093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhaddā Kāpilānī |
E950115
|
entity |
| Predicate | maritalStatusBeforeOrdination |
P101491
|
FINISHED |
| Object | married |
—
|
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: married | Statement: [Bhaddā Kāpilānī, maritalStatusBeforeOrdination, married]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maritalStatusBeforeOrdination Context triple: [Bhaddā Kāpilānī, maritalStatusBeforeOrdination, married]
-
A.
maritalStatusBeforeRenunciation
chosen
Indicates the marital status a person had prior to formally renouncing a role, status, or affiliation.
-
B.
spouseStatusAtMarriage
Indicates the marital status each partner held at the time their marriage to one another was formed.
-
C.
marriageBefore
Indicates that one marriage event occurred earlier in time than another marriage event.
-
D.
spouseBeforeConversion
Indicates that one person was the spouse of another prior to a specified religious or ideological conversion.
-
E.
religiousStatus
Indicates the religious affiliation, role, or standing that an entity holds within a religious context.
- 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_69f76f0124408190bb39c3040734846b |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:33 p.m.