Triple
T29301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bessemer process |
E584
|
entity |
| Predicate | industrialApplication |
P98
|
FINISHED |
| Object | rail production |
—
|
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: rail production | Statement: [Bessemer process, industrialApplication, rail production]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: industrialApplication Context triple: [Bessemer process, industrialApplication, rail production]
-
A.
appliesTo
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
-
B.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
C.
usedFor
chosen
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
D.
usedInInternationalTrade
Indicates that something participates as a good, service, or instrument in commercial exchanges between different countries.
-
E.
environmentType
Indicates the kind or category of environment associated with an entity or situation.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a2490019948190a89bb0910c60d462 |
completed | Feb. 28, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69a2486d40348190b2d21fc444f499a6 |
completed | Feb. 28, 2026, 1:44 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.