Triple
T18021133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pulmonary veins |
E431118
|
entity |
| Predicate | receiveBloodFrom |
P62755
|
FINISHED |
| Object | Lungs |
—
|
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: Lungs | Statement: [Pulmonary veins, receiveBloodFrom, Lungs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: receiveBloodFrom Context triple: [Pulmonary veins, receiveBloodFrom, Lungs]
-
A.
receivedBloodTransfusionFrom
Indicates that one entity has been given blood or blood products from another entity through a transfusion procedure.
-
B.
obtainsBloodFrom
chosen
Indicates that one entity receives or collects blood from another entity.
-
C.
bloodProduced
Indicates that one entity generates or produces blood for another entity or as a result of a process.
-
D.
bloodUsedFor
Indicates that blood is utilized or applied for a particular purpose, function, or process.
-
E.
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).
- 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_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. |
Created at: April 10, 2026, 10:24 a.m.