Triple
T29294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bessemer process |
E584
|
entity |
| Predicate | typicalCapacity |
P1931
|
FINISHED |
| Object | several tons of molten iron per heat |
—
|
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: several tons of molten iron per heat | Statement: [Bessemer process, typicalCapacity, several tons of molten iron per heat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCapacity Context triple: [Bessemer process, typicalCapacity, several tons of molten iron per heat]
-
A.
typicalHeight
Indicates the usual or characteristic height associated with an entity, such as a person, object, or species.
-
B.
canHold
Indicates that one entity has the capacity or ability to contain, support, or carry another entity.
-
C.
typicalEnergyRange
Indicates the usual or characteristic range of energy values associated with an entity, process, or interaction.
-
D.
passengersCountApproximate
Indicates that the number of passengers involved is given as an approximate or estimated count rather than an exact figure.
-
E.
typicalKey
Indicates that the referenced key is the standard or most commonly used key associated with an entity or context.
- 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_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. |
| PDg | Predicate description generation | batch_69a248fef2b881908180bd4e32e58cb5 |
completed | Feb. 28, 2026, 1:46 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.