Triple
T3722664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KSU |
E81673
|
entity |
| Predicate | firstCharacterType |
P51442
|
FINISHED |
| Object | letter |
—
|
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: letter | Statement: [KSU, firstCharacterType, letter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstCharacterType Context triple: [KSU, firstCharacterType, letter]
-
A.
firstLetter
Indicates that one entity is the initial character or starting letter of another entity (typically a string or word).
-
B.
hasTypicalCharacterType
Indicates that an entity is commonly associated with or exemplified by a particular type of character or persona.
-
C.
firstStageType
Indicates that one entity is the type or category of the first stage or initial phase associated with another entity.
-
D.
firstProductionType
Indicates the type or category of the initial production associated with an entity, such as its first manufacturing, creation, or release process.
-
E.
followsCharacterType
Indicates that one character’s behavior, role, or traits are patterned after, derived from, or constrained by a specified character type.
- 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_69ad8b1b7ef081908d2d381bbf54985a |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adca9ea1688190b3b8414d77960e8f |
completed | March 8, 2026, 7:14 p.m. |
| PD | Predicate disambiguation | batch_69adc0436e508190909ec4a3e8443aef |
completed | March 8, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69adc48ec1a081909af0ff9f267c0ffe |
completed | March 8, 2026, 6:48 p.m. |
Created at: March 8, 2026, 3:34 p.m.