Triple
T5420739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One Fish, Two Fish, Red Fish, Blue Fish |
E121240
|
entity |
| Predicate | waterExposure |
P63558
|
FINISHED |
| Object | riders may get wet |
—
|
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: riders may get wet | Statement: [One Fish, Two Fish, Red Fish, Blue Fish, waterExposure, riders may get wet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterExposure Context triple: [One Fish, Two Fish, Red Fish, Blue Fish, waterExposure, riders may get wet]
-
A.
waterType
Indicates the specific kind or category of water associated with an entity (e.g., fresh, salt, brackish).
-
B.
hasWaterActivity
Indicates that one entity possesses, exhibits, or is characterized by a particular level or type of water-related activity (such as moisture content, water availability, or water-based processes).
-
C.
hasNearbyWater
Indicates that one entity is located close to a body of water associated with or relevant to another entity.
-
D.
waterContains
Indicates that a body or volume of water holds, includes, or has within it a specified substance, object, or entity.
-
E.
waterFilled
Indicates that one entity is filled or occupied with water, typically to a certain level or capacity.
- 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_69bd463b58d88190b258261573de9e91 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd87eac41481908a4982db5d119edd |
completed | March 20, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69bd8469f5e48190bbe5c8bdfe8925ea |
completed | March 20, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69bd8741e8588190863fd5cfb559136d |
completed | March 20, 2026, 5:43 p.m. |
Created at: March 20, 2026, 2:06 p.m.