Triple
T31384788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bituminous coal fields of Pennsylvania |
E800565
|
entity |
| Predicate | carbonContent |
P171679
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Bituminous coal fields of Pennsylvania, carbonContent, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: carbonContent Context triple: [Bituminous coal fields of Pennsylvania, carbonContent, high]
-
A.
carbonateContent
Indicates the proportion or amount of carbonate present in a given material or sample.
-
B.
hasTypicalCarbonContentRange
Indicates the usual lower and upper bounds of carbon content typically found in or associated with an entity.
-
C.
hydrogenContent
Indicates the amount or proportion of hydrogen present in a given substance, material, or system.
-
D.
numberOfCarbonAtoms
Indicates the count of carbon atoms present in a specified chemical entity or structure.
-
E.
hasCarbonToNitrogenRatio
Indicates the proportional relationship between the amount of carbon and the amount of nitrogen present in or associated with an entity.
- 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_69f224e9d7048190b0cc20f9071bd3e4 |
completed | April 29, 2026, 3:34 p.m. |
| NER | Named-entity recognition | batch_69f6a1ac56b88190a820434b65c9fa23 |
completed | May 3, 2026, 1:15 a.m. |
| PD | Predicate disambiguation | batch_69f69fe463248190aa78128abeab1183 |
completed | May 3, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69f6a0e920cc8190a943fdd0594906c5 |
completed | May 3, 2026, 1:12 a.m. |
Created at: April 29, 2026, 9:19 p.m.