Triple
T9782991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PAL device |
E237420
|
entity |
| Predicate | commonApplication |
P90630
|
FINISHED |
| Object | address decoding |
—
|
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: address decoding | Statement: [PAL device, commonApplication, address decoding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonApplication Context triple: [PAL device, commonApplication, address decoding]
-
A.
commonOn
Indicates that two or more entities share the same location, context, or medium where they are present or occur together.
-
B.
exampleApplication
Indicates that something serves as a representative or illustrative instance of how an application is used or functions.
-
C.
commonIn
Indicates that something frequently occurs, appears, or is found within a specified context, group, or environment.
-
D.
commonFor
Indicates that something is typical, usual, or frequently occurring for a given entity or context.
-
E.
commonAttribute
Indicates that two or more entities share the same specified attribute or property.
- 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_69ca84da927881909bda80caecad6010 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda1b5714481908bf74b8bf3e4e6e8 |
completed | April 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69cd03d77c6c81909b675955bf113320 |
completed | April 1, 2026, 11:39 a.m. |
| PDg | Predicate description generation | batch_69cd06aa8bc88190904be19c8953def8 |
completed | April 1, 2026, 11:51 a.m. |
Created at: March 30, 2026, 8:27 p.m.