Triple
T27662405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chubby lock service |
E697153
|
entity |
| Predicate | lockGranularity |
P82884
|
FINISHED |
| Object | file-level locks |
—
|
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: file-level locks | Statement: [Chubby lock service, lockGranularity, file-level locks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lockGranularity Context triple: [Chubby lock service, lockGranularity, file-level locks]
-
A.
controlGranularity
Indicates the level of detail or fineness with which control or regulation is applied within a given process or system.
-
B.
reservationGranularity
Indicates the level of detail or unit (such as time, quantity, or capacity) at which a reservation can be specified or managed.
-
C.
executionGranularity
Indicates the level of detail or subdivision at which an operation, task, or process is carried out or controlled.
-
D.
scalingGranularity
Indicates the level of detail or resolution at which a quantity, process, or system is adjusted or scaled.
-
E.
accessGranularity
chosen
Indicates the level of detail or scope at which access or permissions are defined and applied within a system or resource.
- 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_69ef590b85a4819083ec7c12bd3c9c10 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f634a183bc8190bdb59700f8f0a16e |
completed | May 2, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69f62c1a92648190835a2c5250d8c758 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 2:37 p.m.