Triple
T13099718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nydeggbrücke |
E310685
|
entity |
| Predicate | hasLoadType |
P108035
|
FINISHED |
| Object | road traffic |
—
|
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: road traffic | Statement: [Nydeggbrücke, hasLoadType, road traffic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLoadType Context triple: [Nydeggbrücke, hasLoadType, road traffic]
-
A.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
-
B.
hasPackageType
Indicates that an entity is associated with or classified under a particular type or category of package.
-
C.
hasReadingType
Indicates that an entity is associated with a specific category or mode of reading, such as a particular interpretation, format, or type of reading measurement.
-
D.
hasTaskType
Indicates that an entity is associated with or classified under a specific type or category of task.
-
E.
hasLevelType
Indicates that an entity is associated with a specific type or category of level (e.g., difficulty, hierarchy, or stage).
- 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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d981500d34819097037b3c3c33627b |
completed | April 10, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69d98041a3548190a05ddd83dbb660fa |
completed | April 10, 2026, 10:57 p.m. |
| PDg | Predicate description generation | batch_69d98134df64819084a5674f9475dcc2 |
completed | April 10, 2026, 11:01 p.m. |
Created at: April 9, 2026, 9:04 p.m.