Triple
T16332308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hōjō Tokimasa |
E396583
|
entity |
| Predicate | tookTheTonsure |
P108515
|
FINISHED |
| Object | after retirement |
—
|
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: after retirement | Statement: [Hōjō Tokimasa, tookTheTonsure, after retirement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tookTheTonsure Context triple: [Hōjō Tokimasa, tookTheTonsure, after retirement]
-
A.
monasticTonsure
chosen
Indicates the act or state of a person being ritually shaved or having their hair cut as part of entering or belonging to a monastic or religious order.
-
B.
tookReligiousVows
Indicates that an entity formally committed to a religious life by taking recognized vows within a religious tradition.
-
C.
tookReligiousVowsOn
Indicates that an entity formally committed to religious vows on a specific date or occasion.
-
D.
wasMonkOf
Indicates that a person was a member or monk belonging to a particular religious order, monastery, or monastic community.
-
E.
tookSannyasaFrom
Indicates that one entity formally renounced worldly life and accepted the monastic or ascetic order under the guidance or authority 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2c4e0b1388190824b286e8452fb32 |
completed | April 17, 2026, 11:40 p.m. |
| PD | Predicate disambiguation | batch_69e226eba9b48190af6e80d3d1c2aed3 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:07 a.m.