Triple
T12136291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paraíso metro station |
E289064
|
entity |
| Predicate | hasServiceFrequencyCategory |
P28499
|
FINISHED |
| Object | high frequency |
—
|
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: high frequency | Statement: [Paraíso metro station, hasServiceFrequencyCategory, high frequency]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasServiceFrequencyCategory Context triple: [Paraíso metro station, hasServiceFrequencyCategory, high frequency]
-
A.
hasFrequencyCategory
chosen
Indicates that something is associated with a particular classification of how often it occurs or is used.
-
B.
hasFrequentServices
Indicates that one entity regularly provides or receives services from another entity at short or recurring intervals.
-
C.
serviceFrequencyContext
Indicates the contextual conditions or circumstances under which a service’s frequency is defined, applied, or interpreted.
-
D.
serviceFrequencyType
Indicates how often a service occurs or is scheduled within a given time period.
-
E.
hasFrequencyCoverage
Indicates that one entity provides, supports, or is applicable across a specified range or set of frequencies associated with another entity.
- 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91841615c819097f20a7447a1b8f4 |
completed | April 10, 2026, 3:33 p.m. |
| PD | Predicate disambiguation | batch_69d91508f8008190b3a90ec0bf0953ca |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:49 p.m.