Triple
T31996356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catholic nuns |
E817000
|
entity |
| Predicate | formationLeadsTo |
P27937
|
FINISHED |
| Object | perpetual vows |
—
|
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: perpetual vows | Statement: [Catholic nuns, formationLeadsTo, perpetual vows]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formationLeadsTo Context triple: [Catholic nuns, formationLeadsTo, perpetual vows]
-
A.
canLeadTo
Indicates that one entity, condition, or event has the potential to cause, result in, or bring about another.
-
B.
trainingLeadsTo
chosen
Indicates that a process of training results in or brings about a particular outcome, state, or effect.
-
C.
resolutionLeadsTo
Indicates that achieving a particular resolution or decision directly brings about or causes a subsequent outcome or state.
-
D.
depictsFormationOf
Indicates that one entity visually represents or illustrates the process by which another entity comes into existence or is formed.
-
E.
ledToConstructionOf
Indicates that one entity caused, initiated, or was the primary reason for the construction or creation of another entity.
- 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_69f348f8002081909a3588758ba94afb |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc53f4f881908dcc698687bbb64d |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 12:13 a.m.