Triple
T20921261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SDMRM |
E515212
|
entity |
| Predicate | isOneOfLargestOfType |
P30645
|
FINISHED |
| Object | model railroad museums in the world |
—
|
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: model railroad museums in the world | Statement: [SDMRM, isOneOfLargestOfType, model railroad museums in the world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOneOfLargestOfType Context triple: [SDMRM, isOneOfLargestOfType, model railroad museums in the world]
-
A.
oneOfLargest
chosen
Indicates that the subject is among the largest members within a specified group or set, but not necessarily the single largest.
-
B.
isOneOfLargestTownsIn
Indicates that a town is among the largest towns within a specified region or area.
-
C.
isLargestOf
Indicates that one entity has the greatest size, extent, or magnitude among a specified set of entities.
-
D.
hasLargestAreaOf
Indicates that the subject entity possesses the greatest area (size of surface or region) compared to the other entities in the specified set or context.
-
E.
madeStateOneOfLargestIn
Indicates that an entity caused a state to become one of the largest within a specified group, category, or region.
- 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_69e0b4f9d5ec8190bb2bd27350ed341c |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6f64e56bc81908aa86f2176fcc0db |
completed | April 21, 2026, 4 a.m. |
| PD | Predicate disambiguation | batch_69e5c9af1fe08190953366a466950140 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:48 p.m.