Triple
T37667461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Action of 23 November 1939 |
E937858
|
entity |
| Predicate | RawalpindiArmament |
P159514
|
FINISHED |
| Object | outdated naval guns |
—
|
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Phrase: outdated naval guns | Statement: [Action of 23 November 1939, RawalpindiArmament, outdated naval guns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: RawalpindiArmament Context triple: [Action of 23 November 1939, RawalpindiArmament, outdated naval guns]
-
A.
armamentCategory
Indicates the classification of a weapon or military equipment according to its type or role in armament systems.
-
B.
combatArm
Indicates that one entity serves as a primary fighting or operational warfare branch or component of another entity (such as an organization or military force).
-
C.
lightArmament
Indicates that an entity is equipped with or characterized by relatively minimal or lightweight weaponry compared to standard or heavy armament.
-
D.
armamentIncludes
chosen
Indicates that a larger weapon system, vehicle, or platform has a specified weapon or piece of equipment as part of its armament.
-
E.
armamentCount
Indicates the number of weapons or armaments associated with an entity.
- 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_69f76ed6df7c8190b018e5baea716ceb |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba9e27d0c81908342e28f016d221a |
completed | May 6, 2026, 8:51 p.m. |
| PD | Predicate disambiguation | batch_69fba887821c8190ae93ef1dd389e9c8 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:18 p.m.