Triple
T24279513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | tanpura |
E605500
|
entity |
| Predicate | hasTypicalStringCount |
P30141
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [tanpura, hasTypicalStringCount, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalStringCount Context triple: [tanpura, hasTypicalStringCount, 4]
-
A.
hasCommonStringCount
Indicates that two entities share a specified number of identical string values in common.
-
B.
hasStrings
Indicates that an entity possesses or is associated with one or more strings (such as string-like components, text values, or string elements).
-
C.
numberOfStrings
chosen
Indicates the quantity of strings associated with or contained by an entity.
-
D.
hasApproximateNumberOfLetters
Indicates that an entity is associated with a number that roughly, but not exactly, corresponds to the count of letters it contains.
-
E.
hasLetterCount
Indicates that an entity is associated with a specific number representing how many letters it contains.
- 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_69e2954707dc8190915551eb114cfff6 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28f51050481908a9bd3c586702057 |
completed | April 29, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69f1c457a2908190993824395b3c365d |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:07 a.m.