Triple
T10328834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CountQueuingStrategy |
E242827
|
entity |
| Predicate | queueMetricBasis |
P93430
|
FINISHED |
| Object | chunk count |
—
|
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: chunk count | Statement: [CountQueuingStrategy, queueMetricBasis, chunk count]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: queueMetricBasis Context triple: [CountQueuingStrategy, queueMetricBasis, chunk count]
-
A.
queueType
Indicates the classification or category of a queue that specifies how items in it are organized, prioritized, or processed.
-
B.
queueLength
Indicates the current number of items or entities waiting in a queue.
-
C.
queueTypical
Indicates that an entity is in or follows a standard or commonly expected queueing order or behavior relative to others.
-
D.
queueLocation
Indicates the place or position where an entity is arranged to wait in a queue or line.
-
E.
queueRelationship
Indicates a relationship where one entity is placed in an ordered waiting line relative to others, typically to await processing or access.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7cfd54c8190b6f88598339536d1 |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f64a648190a79980d647898eb0 |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d7cada7881908beba55a1dc9ecb9 |
completed | April 7, 2026, 10:09 a.m. |
Created at: April 6, 2026, 11:52 a.m.