Triple
T10869031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Li |
E256602
|
entity |
| Predicate | hasCoreMeaning |
P92178
|
FINISHED |
| Object | proper rites and rituals |
—
|
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: proper rites and rituals | Statement: [Li, hasCoreMeaning, proper rites and rituals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoreMeaning Context triple: [Li, hasCoreMeaning, proper rites and rituals]
-
A.
hasMean
Indicates that one entity possesses, exhibits, or is characterized by a particular mean value or average.
-
B.
hasLiteralMeaning
Indicates that one entity expresses the direct, explicit meaning or sense of another entity (such as a word, phrase, or symbol).
-
C.
commonMeaning
Indicates that multiple entities share the same or very similar meaning or semantic interpretation.
-
D.
hasMeaningViaJohn
Indicates that something possesses or conveys its meaning specifically through John as the interpretive or mediating agent.
-
E.
basicMeaning
chosen
Indicates that one entity expresses or conveys the fundamental or core meaning of another entity.
- 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75170665881909944f92c2cdbe7e6 |
completed | April 9, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69d70d308dfc81908792f98cfb871392 |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:20 p.m.