Triple
T20205853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Union Pacific Big Boy class locomotives |
E493346
|
entity |
| Predicate | numberSeries |
P61667
|
FINISHED |
| Object | 4000–4024 |
—
|
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: 4000–4024 | Statement: [Union Pacific Big Boy class locomotives, numberSeries, 4000–4024]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberSeries Context triple: [Union Pacific Big Boy class locomotives, numberSeries, 4000–4024]
-
A.
numberOfSeries
Indicates the total count of distinct series associated with or contained within a given entity.
-
B.
number
Indicates that one entity is associated with a specific numerical value or count in relation to another entity or context.
-
C.
seriesGeneration
Indicates that one entity is responsible for creating, originating, or giving rise to a series or sequence of related items, events, or works.
-
D.
hasSeriesNumber
chosen
Indicates that an entity is assigned a specific ordinal or sequence number within a series or ordered set.
-
E.
numericSuffix
Indicates that one entity serves as a numeric ending or trailing number appended to another entity (such as a name, identifier, or string).
- 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_69da6269614c8190bb40475d9d477358 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66d922ebc8190ae012da8ceba74dd |
completed | April 20, 2026, 6:16 p.m. |
| PD | Predicate disambiguation | batch_69e55b14c9d8819095453d0504d9222f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:38 p.m.