Triple
T868608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ISO 9660 |
E18760
|
entity |
| Predicate | level2Feature |
P20332
|
FINISHED |
| Object | longer filenames up to 31 characters |
—
|
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: longer filenames up to 31 characters | Statement: [ISO 9660, level2Feature, longer filenames up to 31 characters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: level2Feature Context triple: [ISO 9660, level2Feature, longer filenames up to 31 characters]
-
A.
featureType
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
-
B.
amenityLevel
Indicates the degree or quality of facilities, services, or conveniences provided in relation to something.
-
C.
withinFeature
Indicates that one entity is spatially contained inside or lies entirely within the bounds of another feature.
-
D.
secondLevelStructure
Indicates a relationship where one structure functions as a secondary or subordinate level within a larger, primary structure.
-
E.
featuresCross
Indicates that one feature or element intersects or passes across another in space or structure.
- 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_69a4938ce8688190a24bdfef82ba7d21 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac7f98908190883f71049092c7c8 |
completed | March 1, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69a4aa87504481909618a6815948da6f |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab498bb0819080e3afb684b504b6 |
completed | March 1, 2026, 9:10 p.m. |
Created at: March 1, 2026, 7:39 p.m.