Triple
T6251576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Appalachian dulcimer |
E140056
|
entity |
| Predicate | hasNumberOfStringsRange |
P30141
|
FINISHED |
| Object | 3–4 strings |
—
|
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: 3–4 strings | Statement: [Appalachian dulcimer, hasNumberOfStringsRange, 3–4 strings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfStringsRange Context triple: [Appalachian dulcimer, hasNumberOfStringsRange, 3–4 strings]
-
A.
numberOfStrings
chosen
Indicates the quantity of strings associated with or contained by an entity.
-
B.
hasLengthRange
Indicates that an entity’s length falls within a specified minimum-to-maximum range.
-
C.
hasApproximateNumberOfLetters
Indicates that an entity is associated with a number that roughly, but not exactly, corresponds to the count of letters it contains.
-
D.
hasNumberOfLetters
Indicates a relationship where an entity is associated with the count of letters it contains.
-
E.
hasNumberOfConsonantLetters
Indicates the relationship between an entity and the count of consonant letters present in its written form.
- 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_69c008b4858c819095b0199114a9a87b |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0633fb2ac8190b71b8e35fa923300 |
completed | March 22, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69c056037bf88190a0a3fe7429345d0b |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:24 p.m.