Triple
T251203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walt Disney World Monorail System |
E5149
|
entity |
| Predicate | hasGauge |
P391
|
FINISHED |
| Object | straddle-beam monorail |
—
|
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: straddle-beam monorail | Statement: [Walt Disney World Monorail System, hasGauge, straddle-beam monorail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGauge Context triple: [Walt Disney World Monorail System, hasGauge, straddle-beam monorail]
-
A.
gaugeGroup
Indicates a relationship where a physical or theoretical model is associated with the gauge group that defines its underlying symmetry structure.
-
B.
hasMeter
Indicates that one entity possesses, uses, or is associated with a specific meter (a measuring device or metrical pattern).
-
C.
hasScale
Indicates that one entity possesses or is characterized by a scale or graduated measurement system related to another entity.
-
D.
trackGauge
chosen
Indicates the distance between the inner faces of the rails in a railway track system.
-
E.
hasStatistics
Indicates that an entity is associated with one or more statistical measures, records, or summaries describing its quantitative properties or performance.
- 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_69a257c4bf688190a46ebbf411ab7473 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d38aba8819081d0958eb60ce27e |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b665f8c8190aac6fcbba2a0eebb |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:54 a.m.