Triple
T18577121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buddhadasa Bhikkhu |
E454013
|
entity |
| Predicate | monasticOrdinationYear |
P22250
|
FINISHED |
| Object | 1926 |
—
|
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: 1926 | Statement: [Buddhadasa Bhikkhu, monasticOrdinationYear, 1926]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: monasticOrdinationYear Context triple: [Buddhadasa Bhikkhu, monasticOrdinationYear, 1926]
-
A.
yearsAsMonk
Indicates the number of years an entity has spent living as a monk.
-
B.
yearOfSannyasa
chosen
Indicates the specific year in which an individual formally took sannyasa (renounced worldly life and entered the renounced order).
-
C.
wasOrdainedAs
Indicates that an entity was formally appointed or consecrated into an official religious or ceremonial role.
-
D.
enteredConventAt
Indicates the point in time or age at which a person formally joined or was admitted into a convent.
-
E.
monasteryEstablished
Indicates that a monastery was founded or formally established at a particular time, place, or by a specific agent.
- 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e543cc94f081909b76c3d488ed5637 |
completed | April 19, 2026, 9:06 p.m. |
| PD | Predicate disambiguation | batch_69e478c98d4c81909d37a0e72c6e7bd0 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:43 a.m.