Triple
T36478013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SECI model |
E898723
|
entity |
| Predicate | describesConversionBetween |
P180354
|
FINISHED |
| Object | tacit knowledge |
—
|
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: tacit knowledge | Statement: [SECI model, describesConversionBetween, tacit knowledge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: describesConversionBetween Context triple: [SECI model, describesConversionBetween, tacit knowledge]
-
A.
isConversion
Indicates that one entity is transformed or converted into another, typically changing its form, type, or representation.
-
B.
convertsBetween
chosen
Indicates a relationship where one entity transforms or translates something from one form, unit, or representation into another.
-
C.
involvesConversionFrom
Indicates that one entity participates in or requires a transformation or change from another entity as its source or starting point.
-
D.
involvesConversionTo
Indicates that one entity undergoes a change of form, type, or state resulting in another entity.
-
E.
methodOfConversion
Indicates the specific process or technique used to transform one form, state, or representation into another.
- 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_69f76e5a0e088190a2b6706aeb41723c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fda94697c4819081291967202248be |
completed | May 8, 2026, 9:13 a.m. |
| PD | Predicate disambiguation | batch_69fda5973fcc8190a57daef31fb70a49 |
completed | May 8, 2026, 8:57 a.m. |
Created at: May 3, 2026, 4:10 p.m.