Triple
T3884853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afrikaansche Galey |
E92914
|
entity |
| Predicate | maritimeDomain |
P51623
|
FINISHED |
| Object | blue-water sailing ship |
—
|
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: blue-water sailing ship | Statement: [Afrikaansche Galey, maritimeDomain, blue-water sailing ship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maritimeDomain Context triple: [Afrikaansche Galey, maritimeDomain, blue-water sailing ship]
-
A.
marineArea
Indicates a relationship where an entity is located in, associated with, or relevant to a specific marine or oceanic area.
-
B.
maritimeActivity
Indicates activities, operations, or behaviors that take place at sea or are directly related to maritime environments and navigation.
-
C.
maritimeUsage
Indicates the extent to which something is used for or involved in maritime activities, such as sea transport, navigation, or ocean-related operations.
-
D.
usedInMaritimeNavigation
Indicates that something is employed as a tool, aid, or reference in the practice of maritime navigation.
-
E.
maritimeSettingFor
Indicates that one entity serves as the maritime or ocean-related environment or backdrop in which another entity is situated or occurs.
- 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_69aed9697de0819087c2559295ff3d12 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeec92cc548190b88b899299e5ccdc |
completed | March 9, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69aee759609c8190985e96ec6d96dedd |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aee80858a481909961a33fb50ff8d1 |
completed | March 9, 2026, 3:32 p.m. |
Created at: March 9, 2026, 3:20 p.m.