Triple
T26848712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cab Forward |
E675994
|
entity |
| Predicate | hasVisibilityBenefit |
P2188
|
FINISHED |
| Object | places crew closer to front of train |
—
|
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: places crew closer to front of train | Statement: [Cab Forward, hasVisibilityBenefit, places crew closer to front of train]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVisibilityBenefit Context triple: [Cab Forward, hasVisibilityBenefit, places crew closer to front of train]
-
A.
hasBenefit
chosen
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
B.
hasVisibility
Indicates that one entity can perceive, view, or access another entity or its information under certain conditions.
-
C.
hasBenefitType
Indicates that an entity is associated with a specific category or type of benefit it provides or receives.
-
D.
hasVisibilityCharacteristic
Indicates that one entity possesses a specific property or quality related to how visible or observable it is.
-
E.
hasBenefitDesign
Indicates that an entity possesses or is associated with a particular benefit-related design or configuration.
- 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_69eee9b8d5e88190a07d3455c0fbb21f |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 27, 2026, 5:14 a.m.