Triple
T9884370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tenman-gū no kami |
E180892
|
entity |
| Predicate | roleInShinto |
P91601
|
FINISHED |
| Object | tutelary deity of students |
—
|
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: tutelary deity of students | Statement: [Tenman-gū no kami, roleInShinto, tutelary deity of students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInShinto Context triple: [Tenman-gū no kami, roleInShinto, tutelary deity of students]
-
A.
roleInKojiki
Indicates the role or function an entity holds within the narrative or structure of the Kojiki.
-
B.
roleAtTemple
Indicates that an entity holds or performs a specific role, function, or position at a particular temple.
-
C.
roleInRitual
Indicates the specific function, position, or responsibility an entity holds within a particular ritual or ceremonial activity.
-
D.
shrineType
Indicates the specific category or kind of shrine associated with an entity.
-
E.
enshrines
Indicates that one entity formally preserves, protects, or honors another by giving it a permanent, often sacred or legally recognized, status.
- 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_69ca828082cc8190a40f8d299caa6545 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb45549488190833200977d558e47 |
completed | April 2, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69cd1d810ed48190a252b70e9390c8f3 |
completed | April 1, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69cd36f112bc81908b473787e702de2f |
completed | April 1, 2026, 3:17 p.m. |
Created at: March 30, 2026, 8:38 p.m.