Triple
T6465917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shichi-Go-San ceremonies |
E142231
|
entity |
| Predicate | ageThreeTerm |
P70958
|
FINISHED |
| Object | san-sai |
—
|
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: san-sai | Statement: [Shichi-Go-San ceremonies, ageThreeTerm, san-sai]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageThreeTerm Context triple: [Shichi-Go-San ceremonies, ageThreeTerm, san-sai]
-
A.
type3Years
Indicates that a relationship, condition, or classification is valid or applies specifically over a three-year period.
-
B.
numberOfAges
Indicates the count of distinct ages associated with an entity or within a specified group or context.
-
C.
hasThirdTerm
Indicates that an entity is associated with or includes a specific third term in an ordered sequence or grouping.
-
D.
ageInPlay
Indicates that an entity’s age is relevant or applicable within the context of a particular play, game, or interactive scenario.
-
E.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
- 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_69c008d3bf4c8190bcf798c5ba9d6fb3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06a1159ec81909bbfa9a9d6fa1616 |
completed | March 22, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69c0673d46a08190bc8bcd29f9555fe7 |
completed | March 22, 2026, 10:03 p.m. |
| PDg | Predicate description generation | batch_69c067da970481908a038995ba7dfb4b |
completed | March 22, 2026, 10:06 p.m. |
Created at: March 22, 2026, 4:49 p.m.