Triple
T31919735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aspidoras |
E814935
|
entity |
| Predicate | preferredWaterHardness |
P158601
|
FINISHED |
| Object | soft to moderately hard |
—
|
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: soft to moderately hard | Statement: [Aspidoras, preferredWaterHardness, soft to moderately hard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: preferredWaterHardness Context triple: [Aspidoras, preferredWaterHardness, soft to moderately hard]
-
A.
waterType
Indicates the specific kind or category of water associated with an entity (e.g., fresh, salt, brackish).
-
B.
waterPH
Indicates the acidity or alkalinity level (pH value) of a given body or sample of water.
-
C.
waterCondition
Indicates the state or quality of water affecting an entity, such as its cleanliness, safety, or suitability for a particular use.
-
D.
hardnessType
chosen
Indicates the specific category or classification of hardness associated with an entity.
-
E.
prefersWater
Indicates a relationship where an entity favors or chooses water over other available options.
- 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_69f348f1df848190851bbfb988da3414 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b1f555fc8190936917339cafcd49 |
completed | May 3, 2026, 2:24 a.m. |
| PD | Predicate disambiguation | batch_69f6aca7081881909e96a8b05ec086bb |
completed | May 3, 2026, 2:02 a.m. |
Created at: May 1, 2026, 12:02 a.m.