Triple
T10029668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dodol Garut |
E204819
|
entity |
| Predicate | hasConsistency |
P91783
|
FINISHED |
| Object | sticky |
—
|
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: sticky | Statement: [Dodol Garut, hasConsistency, sticky]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConsistency Context triple: [Dodol Garut, hasConsistency, sticky]
-
A.
hasWaveConsistency
Indicates that the related entities maintain a stable, coherent pattern or behavior across successive waves, phases, or iterations.
-
B.
isInconsistent
Indicates that there is a logical or factual contradiction within or between the entities or statements involved.
-
C.
typicalConsistency
Indicates that one entity characteristically maintains a regular or expected level of consistency in relation to another entity or context.
-
D.
consistencyModel
Indicates that one entity adheres to, implements, or is governed by a particular consistency model in its behavior or operations.
-
E.
consistentWith
Indicates that one entity does not contradict and is compatible or in agreement with another entity, condition, or set of constraints.
- 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_69ca834d77188190ad645e33e8ca3200 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcde69bd08190a5c79ec8487dfff6 |
completed | April 2, 2026, 2:01 a.m. |
| PD | Predicate disambiguation | batch_69cd4b7cd4208190b2253583ee2f892c |
completed | April 1, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69cd4f8d9b888190b8067bd916dae773 |
completed | April 1, 2026, 5:02 p.m. |
Created at: March 30, 2026, 8:54 p.m.