Triple
T18021092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pulmonary artery |
E431117
|
entity |
| Predicate | bloodTypeCarried |
P129465
|
FINISHED |
| Object | low oxygen content |
—
|
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: low oxygen content | Statement: [Pulmonary artery, bloodTypeCarried, low oxygen content]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bloodTypeCarried Context triple: [Pulmonary artery, bloodTypeCarried, low oxygen content]
-
A.
bloodType
Indicates that one entity has a specific blood group classification (such as A, B, AB, or O, with a positive or negative Rh factor).
-
B.
hasBloodTypeSystem
Indicates that an entity uses or is classified according to a particular blood type classification system (e.g., ABO, Rh).
-
C.
hasBlood
Indicates that one entity possesses or contains the blood of another entity.
-
D.
bloodProduced
Indicates that one entity generates or produces blood for another entity or as a result of a process.
-
E.
receivedBloodTransfusionFrom
Indicates that one entity has been given blood or blood products from another entity through a transfusion procedure.
- 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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b9c299c48190b0cceecf77cb6de9 |
completed | April 19, 2026, 11:17 a.m. |
| PD | Predicate disambiguation | batch_69e3f904b8048190add43883cd7cb191 |
completed | April 18, 2026, 9:35 p.m. |
| PDg | Predicate description generation | batch_69e42d8eefa88190a700c7c1b4213e46 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:24 a.m.