Triple
T6411185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amtrak Acela |
E127707
|
entity |
| Predicate | offersAssignedSeating |
P51117
|
FINISHED |
| Object | yes (First Class) |
—
|
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: yes (First Class) | Statement: [Amtrak Acela, offersAssignedSeating, yes (First Class)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersAssignedSeating Context triple: [Amtrak Acela, offersAssignedSeating, yes (First Class)]
-
A.
hasSeatStatus
Indicates the current condition or availability state of a seat in a given context.
-
B.
individualSeats
Indicates that an entity provides or consists of separate, single-person seating positions rather than shared or bench-style seating.
-
C.
seatsAreAllocatedTo
chosen
Indicates that specific seats are assigned or designated to particular entities (such as people, groups, or bookings).
-
D.
seatingConfiguration
Indicates how seats are arranged or organized relative to each other in a given context.
-
E.
seatWinner
Indicates that a particular candidate or party has won a specific seat (e.g., in an election or contest).
- 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_69c0083723d88190b1e37b19df162c08 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c068d0f2b88190af06c208d8c01d07 |
completed | March 22, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69c060f40ecc8190b1df17b96767675c |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:41 p.m.