Triple
T1395174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tennō Tanjōbi |
E30648
|
entity |
| Predicate | hasReligiousCharacter |
P27703
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [Tennō Tanjōbi, hasReligiousCharacter, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousCharacter Context triple: [Tennō Tanjōbi, hasReligiousCharacter, no]
-
A.
hasReligiousOrigin
Indicates that something originates from, is derived from, or is fundamentally based on a religious tradition, belief system, or practice.
-
B.
hasReligiousTheme
Indicates that something (such as a work, event, or object) centrally involves or expresses religious ideas, symbols, practices, or narratives.
-
C.
hasReligiousOrganization
Indicates that an entity is associated with, governed by, or belongs to a specific religious organization.
-
D.
hasReligiousMovement
Indicates that an entity is associated with, follows, or is characterized by a particular religious movement.
-
E.
bearerReligion
Indicates that a bearer (such as a person or entity) adheres to, practices, or is associated with a particular religion.
- 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_69a498fd4e408190bd73eca30ea9754c |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c37e60388190a8efcb345be7a1b9 |
completed | March 1, 2026, 10:53 p.m. |
| PD | Predicate disambiguation | batch_69a4bf017f8081908572121560ec621f |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c13270d8819081d8ee1be34cabf5 |
completed | March 1, 2026, 10:44 p.m. |
Created at: March 1, 2026, 7:59 p.m.