Triple
T6592212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NOAA Ship Reuben Lasker |
E148388
|
entity |
| Predicate | specialDesignFor |
P40514
|
FINISHED |
| Object | acoustic fisheries surveys |
—
|
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: acoustic fisheries surveys | Statement: [NOAA Ship Reuben Lasker, specialDesignFor, acoustic fisheries surveys]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: specialDesignFor Context triple: [NOAA Ship Reuben Lasker, specialDesignFor, acoustic fisheries surveys]
-
A.
designsFor
chosen
Indicates that one entity creates or plans something specifically intended to serve, suit, or be used by another entity.
-
B.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
C.
custom
Indicates that something is specially created, configured, or tailored for a particular purpose, context, or user rather than being standard or generic.
-
D.
specialAppearance
Indicates that an entity makes a notable or exceptional appearance distinct from its usual or regular presence.
-
E.
designedFeature
Indicates that one entity is a feature or component intentionally planned, created, or specified by another entity as part of a design.
- 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_69c687e7b8688190811ffee72e096468 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c07cdf048190945ca5810fb1de88 |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6acfb462481909cb7aff5af4bca9d |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:55 p.m.