Triple
T475937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maine Narrow Gauge Railroad Museum |
E9060
|
entity |
| Predicate | trackGaugeCategory |
P391
|
FINISHED |
| Object | narrow gauge |
—
|
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: narrow gauge | Statement: [Maine Narrow Gauge Railroad Museum, trackGaugeCategory, narrow gauge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trackGaugeCategory Context triple: [Maine Narrow Gauge Railroad Museum, trackGaugeCategory, narrow gauge]
-
A.
trackGauge
chosen
Indicates the distance between the inner faces of the rails in a railway track system.
-
B.
trackType
Indicates the specific kind or category of track associated with an entity, such as its functional or physical classification.
-
C.
tracks
Indicates that one entity monitors, follows, or keeps a record of another entity’s state, behavior, or progress over time.
-
D.
gaugeGroup
Indicates a relationship where a physical or theoretical model is associated with the gauge group that defines its underlying symmetry structure.
-
E.
rankingCategory
Indicates the classification or type of ranking under which an entity is evaluated or ordered.
- 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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f03b5e5081908ee3dba9d19a6871 |
completed | Feb. 28, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69a2edeed31881908cf43beed410572d |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.