Triple
T2672477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amtrak Capitol Limited |
E55777
|
entity |
| Predicate | trainNumbers |
P30411
|
FINISHED |
| Object | 29 |
—
|
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: 29 | Statement: [Amtrak Capitol Limited, trainNumbers, 29]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainNumbers Context triple: [Amtrak Capitol Limited, trainNumbers, 29]
-
A.
trainCount
Indicates the number of trains associated with a given entity, context, or time period.
-
B.
railwayLineNumber
Indicates the identifying number assigned to a specific railway line within a rail network.
-
C.
trainNumberDirection
Indicates the specific direction in which a train, identified by its train number, is traveling or scheduled to travel.
-
D.
usesTrainNumber
chosen
Indicates that one entity operates, identifies, or references another entity by a specific train number.
-
E.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
- 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_69ab49e54de48190be708cd1cf8be073 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd98f98908190b5c6fb38d3d4367a |
completed | March 7, 2026, 7:53 a.m. |
| PD | Predicate disambiguation | batch_69abd8190ad481908f3e14ac84d0940a |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:54 p.m.