Triple
T16130663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franklin Avenue Station |
E391385
|
entity |
| Predicate | hasPassengerAmenity |
P121590
|
FINISHED |
| Object | benches |
—
|
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: benches | Statement: [Franklin Avenue Station, hasPassengerAmenity, benches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerAmenity Context triple: [Franklin Avenue Station, hasPassengerAmenity, benches]
-
A.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
-
B.
hasPassengerArea
Indicates that an object or vehicle includes a designated area intended for carrying passengers.
-
C.
hasPassengerOnlyService
Indicates that the service provided involves only the transportation of passengers, with no freight or cargo component.
-
D.
hasLoungeCar
Indicates that something includes or is equipped with a lounge car as part of its composition or configuration.
-
E.
hasOnboardLuggageSpace
Indicates that an entity provides or includes dedicated space for carrying luggage on board.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2020829e88190b51ab32d22cf0259 |
completed | April 17, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69e1828518c48190a8ef3aaa46a1f639 |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e183b9d3f08190953ada68f4272996 |
completed | April 17, 2026, 12:50 a.m. |
Created at: April 10, 2026, 5:01 a.m.