Triple
T16513807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michigan Line |
E401127
|
entity |
| Predicate | hasSignaling |
P63209
|
FINISHED |
| Object | positive train control on many segments |
—
|
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: positive train control on many segments | Statement: [Michigan Line, hasSignaling, positive train control on many segments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSignaling Context triple: [Michigan Line, hasSignaling, positive train control on many segments]
-
A.
usesSignaling
Indicates that one entity communicates or coordinates with another by emitting, transmitting, or interpreting signals.
-
B.
usesSignalingChannel
Indicates that one entity communicates or exchanges information with another through a specific signaling channel or medium.
-
C.
hasSign
Indicates that an entity possesses, displays, or is associated with a particular sign or symbol.
-
D.
compatibleWithSignaling
Indicates that one entity can correctly interpret, process, or operate using the signaling mechanisms, protocols, or formats employed by another entity.
-
E.
usesSignallingPractice
chosen
Indicates that one entity employs or follows a particular signalling practice in its communication or behavior.
- 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_69d88381f6148190819958a038be990e |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e78d4848190a55de9902115b1b2 |
completed | April 18, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69e296995d388190b88ebe189dce890d |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:14 a.m.