Triple
T35479181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wanamaker Grand Court Organ |
E1025421
|
entity |
| Predicate | hasNumberOfStops |
P198611
|
FINISHED |
| Object | over 400 |
—
|
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: over 400 | Statement: [Wanamaker Grand Court Organ, hasNumberOfStops, over 400]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfStops Context triple: [Wanamaker Grand Court Organ, hasNumberOfStops, over 400]
-
A.
hasStops
Indicates that a route, service, or journey includes one or more intermediate stopping points at specified locations.
-
B.
numberOfIntermediateStops
Indicates the count of stops or pauses that occur between the starting point and the final destination in a journey or process.
-
C.
hasStopoverState
Indicates that an entity’s journey or process includes an intermediate stop or temporary state before reaching its final destination or outcome.
-
D.
stopsAtFewerStationsThan
Indicates that one transit service or route makes stops at a smaller number of stations than another transit service or route.
-
E.
heritageTrailNumberOfStops
Indicates the number of designated stops or points of interest along a heritage trail.
- 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_69f76dfadba0819083456aadcd6864ea |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fef5cf8da881908260ec633830375d |
completed | May 9, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_69fef455e40481909861c82007b79bc0 |
completed | May 9, 2026, 8:46 a.m. |
| PDg | Predicate description generation | batch_69fef5cec8208190b85665ab6a511a08 |
completed | May 9, 2026, 8:52 a.m. |
Created at: May 3, 2026, 4:04 p.m.