Triple
T4691751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tram 28 route |
E104048
|
entity |
| Predicate | typicalCrowding |
P18989
|
FINISHED |
| Object | often crowded |
—
|
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: often crowded | Statement: [Tram 28 route, typicalCrowding, often crowded]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCrowding Context triple: [Tram 28 route, typicalCrowding, often crowded]
-
A.
hasCrowdLevel
chosen
Indicates the degree or intensity of how crowded a place, event, or situation is.
-
B.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
C.
hasHeavyPassengerTraffic
Indicates that an entity experiences a high volume of passenger movement or usage over a given period.
-
D.
typicalEdge
Indicates a standard or representative connection between two entities, as opposed to a special or exceptional type of edge.
-
E.
typicalConsistency
Indicates that one entity characteristically maintains a regular or expected level of consistency in relation to another entity or context.
- 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_69bd43df91f481908e9add1b617b60ef |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd66059bfc8190885d26d05dd38df1 |
completed | March 20, 2026, 3:21 p.m. |
| PD | Predicate disambiguation | batch_69bd6219da948190bbbb50f08573ab4d |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:16 p.m.