Triple
T28380941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Self (Marc Quinn) |
E718885
|
entity |
| Predicate | bloodVolumePerWork |
P165148
|
FINISHED |
| Object | several liters of blood |
—
|
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 liters of blood | Statement: [Self (Marc Quinn), bloodVolumePerWork, several liters of blood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bloodVolumePerWork Context triple: [Self (Marc Quinn), bloodVolumePerWork, several liters of blood]
-
A.
bloodUsedFor
Indicates that blood is utilized or applied for a particular purpose, function, or process.
-
B.
bloodStatus
Indicates the classification of an entity based on the type or purity of its blood or lineage.
-
C.
bloodProduced
Indicates that one entity generates or produces blood for another entity or as a result of a process.
-
D.
bloodFlowsThrough
Indicates that blood moves within or along the interior of a specified anatomical structure or pathway.
-
E.
pumpingPower
Indicates the rate at which energy is supplied or transferred by a pump to move a fluid or medium.
- 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_69eff6ee5afc8190bd7375a29f0cc6c6 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f65705a3048190a3728b695ba2ae65 |
completed | May 2, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69f651a931748190a637e631a52bbfaa |
completed | May 2, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69f6562ef4e4819082ce6abd41b74dc5 |
completed | May 2, 2026, 7:53 p.m. |
Created at: April 28, 2026, 1:06 a.m.