Triple
T31046722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hugh I, Duke of Burgundy |
E791146
|
entity |
| Predicate | tookMonasticVowsAt |
P40813
|
FINISHED |
| Object | Cluny Abbey |
—
|
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: Cluny Abbey | Statement: [Hugh I, Duke of Burgundy, tookMonasticVowsAt, Cluny Abbey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tookMonasticVowsAt Context triple: [Hugh I, Duke of Burgundy, tookMonasticVowsAt, Cluny Abbey]
-
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.
vowedCelibacyWith
Indicates a mutual commitment between entities to abstain from sexual or romantic relationships, typically formalized as a shared vow of celibacy.
-
E.
enteredConvent
Indicates that a person has joined and been admitted into a religious convent as a member.
- 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_69f224ca2fa881908a3ac5fedf207b90 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6953cbb5c8190b3f6ee0149c9eecc |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690f13d7481908ddfefe95df2a1c2 |
completed | May 3, 2026, 12:04 a.m. |
Created at: April 29, 2026, 8:59 p.m.