Triple
T7811323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Zealand Division of the Royal Navy |
E180689
|
entity |
| Predicate | wartimeActivity |
P79144
|
FINISHED |
| Object | escorting convoys |
—
|
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: escorting convoys | Statement: [New Zealand Division of the Royal Navy, wartimeActivity, escorting convoys]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wartimeActivity Context triple: [New Zealand Division of the Royal Navy, wartimeActivity, escorting convoys]
-
A.
wartimeUse
Indicates that something is used or employed during a period of war or armed conflict.
-
B.
wartimeGain
Indicates that an entity acquires benefits, resources, or advantages specifically as a result of wartime conditions or activities.
-
C.
wartimeComposition
Indicates that a creative work was composed, written, or otherwise produced during a period of war or armed conflict.
-
D.
wartimeControl
Indicates that one entity exercises authoritative command or governance over another entity specifically during a period of armed conflict or war.
-
E.
wartimeLocation
Indicates the location where an entity is situated or operates during a period of war or armed conflict.
- 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_69ca827f6f148190beca4e245b993506 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78cd1cc8190b4cdd9850e1e2bb7 |
completed | March 30, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69cae91687788190af9cb7aaa996d291 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7855a3c81908b9318f7186fc0c0 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 4:37 p.m.