Triple
T1245891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baltimore and Ohio Railroad |
E26763
|
entity |
| Predicate | laterUsedTechnology |
P25950
|
FINISHED |
| Object | diesel locomotives |
—
|
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: diesel locomotives | Statement: [Baltimore and Ohio Railroad, laterUsedTechnology, diesel locomotives]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterUsedTechnology Context triple: [Baltimore and Ohio Railroad, laterUsedTechnology, diesel locomotives]
-
A.
laterUsedBy
Indicates that something is subsequently utilized or employed by a specified entity at a later time.
-
B.
technologyPioneered
Indicates that an entity was the first or among the first to develop, introduce, or significantly advance a particular technology.
-
C.
alsoUsedBy
Indicates that something is additionally utilized or employed by another entity, beyond any primary or previously mentioned user.
-
D.
technologyLevel
Indicates the degree of technological advancement or sophistication associated with an entity relative to others or to a defined scale.
-
E.
technologyGeneration
Indicates the generational level or era of technology associated with or used by an entity in relation to another.
- F. None of above. chosen
Provenance (4 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_69a4948689d08190b3a4a3f388c02148 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf65c41c8190b4c65e015d1264c0 |
completed | March 1, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69a4bb696a38819095845c84f0241287 |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bce611ec819092cb13d354d0903e |
completed | March 1, 2026, 10:25 p.m. |
Created at: March 1, 2026, 7:47 p.m.