Triple
T13661909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thérèse of Lisieux |
E327017
|
entity |
| Predicate | enteredReligiousLife |
P40813
|
FINISHED |
| Object | 1888 |
—
|
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: 1888 | Statement: [Thérèse of Lisieux, enteredReligiousLife, 1888]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enteredReligiousLife Context triple: [Thérèse of Lisieux, enteredReligiousLife, 1888]
-
A.
tookReligiousVowsOn
Indicates that an entity formally committed to religious vows on a specific date or occasion.
-
B.
tookReligiousVows
chosen
Indicates that an entity formally committed to a religious life by taking recognized vows within a religious tradition.
-
C.
forcedIntoMonasticLifeBy
Indicates that one entity compelled another, against their will or under strong pressure, to enter and live a monastic or religious life.
-
D.
enteredConventAt
Indicates the point in time or age at which a person formally joined or was admitted into a convent.
-
E.
convertedToReligion
Indicates that an entity adopted or changed to a particular religion, typically from a previous belief system or lack thereof.
- 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc620df208190afaccf3ddd10aa60 |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8a027081908d8f884b89707a5e |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:52 p.m.