Triple
T2270885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acipenseriformes |
E50653
|
entity |
| Predicate | sensoryFeature |
P24994
|
FINISHED |
| Object | well-developed electroreception in some species |
—
|
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: well-developed electroreception in some species | Statement: [Acipenseriformes, sensoryFeature, well-developed electroreception in some species]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sensoryFeature Context triple: [Acipenseriformes, sensoryFeature, well-developed electroreception in some species]
-
A.
sensitivityFeature
chosen
Indicates a relationship where one entity functions as a sensitivity-related characteristic, parameter, or attribute of another entity.
-
B.
providesSensoryEffects
Indicates that one entity causes or contributes to sensory experiences or perceptions in another entity.
-
C.
fruitCharacteristic
Indicates that a specified characteristic or property is attributed to a particular fruit.
-
D.
cuisineFeature
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
-
E.
primarySense
Indicates that one sense or meaning of an entity is designated as its main or most central sense among possible alternatives.
- 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_69a88b05910c8190a9a2b1ff230c85f9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc39c6ff0819081a07696f1c29990 |
completed | March 7, 2026, 6:20 a.m. |
| PD | Predicate disambiguation | batch_69abbdb7719081909143efa8f48df4e4 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.