Triple
T17350744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mansonia |
E421803
|
entity |
| Predicate | bloodMealRequirement |
P127148
|
FINISHED |
| Object | females require blood meal for egg development |
—
|
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: females require blood meal for egg development | Statement: [Mansonia, bloodMealRequirement, females require blood meal for egg development]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bloodMealRequirement Context triple: [Mansonia, bloodMealRequirement, females require blood meal for egg development]
-
A.
bloodMealHosts
Indicates that one organism serves as a source of blood for another organism’s feeding.
-
B.
intendedFood
Indicates that one entity is the food item that another entity plans or is meant to eat or consume.
-
C.
isEatenIn
Indicates that one entity (typically food) is consumed within the context, location, or occasion specified by another entity.
-
D.
intendedMeal
Indicates that one entity is the meal that another entity plans or expects to eat.
-
E.
feedingStructure
Indicates a relationship where one entity serves as the anatomical or mechanical structure used by another entity to obtain or ingest food.
- 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_69d889d520008190a26917a95bf1c2ea |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a2ca0708190aae8306ec3a6f2a7 |
completed | April 19, 2026, 2:13 a.m. |
| PD | Predicate disambiguation | batch_69e3b02662d08190a07d0fb5c04b6f33 |
completed | April 18, 2026, 4:24 p.m. |
| PDg | Predicate description generation | batch_69e3b2a225b08190a50f984caa6513b9 |
completed | April 18, 2026, 4:34 p.m. |
Created at: April 10, 2026, 5:44 a.m.