Triple
T8198177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryann |
E191487
|
entity |
| Predicate | meaningInferredFromRyan |
P81452
|
FINISHED |
| Object | little king |
—
|
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: little king | Statement: [Ryann, meaningInferredFromRyan, little king]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meaningInferredFromRyan Context triple: [Ryann, meaningInferredFromRyan, little king]
-
A.
possibleMeaning
Indicates that something may plausibly represent, signify, or be interpreted as a particular meaning or sense.
-
B.
hasMeaningViaJohn
Indicates that something possesses or conveys its meaning specifically through John as the interpretive or mediating agent.
-
C.
logicalMeaning
Indicates that one entity expresses, encodes, or conveys the logical content, implication, or formal meaning of another.
-
D.
oniMeaning
Indicates that one entity expresses or conveys the meaning or sense of another entity (such as a word, phrase, or symbol).
-
E.
ribbonMeaning
Indicates that one entity symbolically represents, commemorates, or raises awareness for a cause, event, or concept through the use of a ribbon.
- 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_69ca82c6e9548190a4c5ca14516e4417 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb5c2341f881908be59c378896e5bc |
completed | March 31, 2026, 5:31 a.m. |
| PD | Predicate disambiguation | batch_69cb36aac86081909b83636e352e0ced |
completed | March 31, 2026, 2:51 a.m. |
| PDg | Predicate description generation | batch_69cb46635424819085d086972b264280 |
completed | March 31, 2026, 3:58 a.m. |
Created at: March 30, 2026, 5:42 p.m.