Triple
T19314646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhaisajyaguru |
E483062
|
entity |
| Predicate | vowCount |
P135553
|
FINISHED |
| Object | 12 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: 12 vows | Statement: [Bhaisajyaguru, vowCount, 12 vows]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vowCount Context triple: [Bhaisajyaguru, vowCount, 12 vows]
-
A.
hasNumberOfVowelLetters
Indicates that an entity is associated with a specific count of vowel letters it contains.
-
B.
hasNumberOfVowelSigns
Indicates the count of vowel signs associated with or present in a given linguistic unit (such as a character, syllable, or word).
-
C.
containsVowelLetters
Indicates that the subject includes one or more vowel letters within its sequence of characters.
-
D.
hasVowelInventorySize
Indicates that an entity is associated with a specific number of distinct vowel sounds in its phonological system.
-
E.
vowPractice
Indicates that an entity engages in or upholds a particular vow, promise, or solemn commitment as an ongoing practice.
- F. None of above. chosen
Provenance (4 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_69d8e8d04d5c8190baa816986f2b1d1e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e604cfec8c8190a118b327b1418150 |
completed | April 20, 2026, 10:49 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0ef66881909d489d634eee817a |
completed | April 19, 2026, 1:47 p.m. |
| PDg | Predicate description generation | batch_69e4e4709d4481908c280cdd2ac18977 |
completed | April 19, 2026, 2:19 p.m. |
Created at: April 10, 2026, 1:32 p.m.