Triple
T24358901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Castle Cary railway station |
E614001
|
entity |
| Predicate | hasEventTrafficFor |
P155913
|
FINISHED |
| Object | Glastonbury Festival |
—
|
NE NERFINISHED |
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: Glastonbury Festival | Statement: [Castle Cary railway station, hasEventTrafficFor, Glastonbury Festival]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEventTrafficFor Context triple: [Castle Cary railway station, hasEventTrafficFor, Glastonbury Festival]
-
A.
hasPortTraffic
Indicates that there is a flow or volume of traffic (such as ships, cargo, or passengers) associated with a particular port.
-
B.
hasTrafficPattern
Indicates that there is a characteristic or recurring flow of traffic associated with an entity, such as its typical volume, direction, or timing of movement.
-
C.
hasTrafficFunction
Indicates that an entity performs, supports, or is assigned a specific function or role related to traffic management or control.
-
D.
hasEventFrequency
Indicates how often a particular event occurs within a given time period.
-
E.
hasDailyTraffic
Indicates that an entity experiences or is associated with a certain amount or pattern of traffic on a daily basis.
- 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_69e2d7dfe7f08190b7a1f3a36483ab05 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2934bcc608190b86bc091474bb259 |
completed | April 29, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69f287bb1b2c81909c2e7fcc392ad143 |
completed | April 29, 2026, 10:35 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2 a.m.