Triple
T15617306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montauk station |
E375448
|
entity |
| Predicate | hasSeasonalRidershipPeak |
P119443
|
FINISHED |
| Object | summer months |
—
|
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: summer months | Statement: [Montauk station, hasSeasonalRidershipPeak, summer months]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeasonalRidershipPeak Context triple: [Montauk station, hasSeasonalRidershipPeak, summer months]
-
A.
dailyRidershipPeak
Indicates that the relationship specifies the highest number of riders or users recorded for a service or system within a single day.
-
B.
annualRidership
Indicates the total number of passengers who use a transportation service over the course of one year.
-
C.
populationPeakPeriod
Indicates the time period during which a population reached its highest recorded level.
-
D.
dailyRidership
Indicates the typical number of people who use or ride a given transportation service each day.
-
E.
dailyRidershipCategory
Indicates the classification of an entity based on the typical number of riders it serves per day.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e980b748190b43c0b650bf1e629 |
completed | April 16, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69deda844af081909e658ebc9d9b403d |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f3016c8190ac68d76e65e07af4 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:13 a.m.