Triple
T8898316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oryzoborus maximiliani |
E211860
|
entity |
| Predicate | hasBlood |
P85124
|
FINISHED |
| Object | warm-blooded |
—
|
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: warm-blooded | Statement: [Oryzoborus maximiliani, hasBlood, warm-blooded]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBlood Context triple: [Oryzoborus maximiliani, hasBlood, warm-blooded]
-
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.
obtainsBloodFrom
Indicates that one entity receives or collects blood from another entity.
-
C.
hasBloodPigment
Indicates that an organism possesses a specific pigment in its blood responsible for coloration and often for oxygen transport.
-
D.
bloodStatus
Indicates the classification of an entity based on the type or purity of its blood or lineage.
-
E.
hasBloodTypeSystem
Indicates that an entity uses or is classified according to a particular blood type classification system (e.g., ABO, Rh).
- 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_69ca83918d3081909b326fa3750cb8c8 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc642618908190b3df50cbbabff93d |
completed | April 1, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2bfb38819083d5eb1af8ccf4d6 |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5cffe8ec819084c12770fe0578f2 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:54 p.m.