Triple
T1205396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Packard V-1650 |
E25875
|
entity |
| Predicate | warProduction |
P25559
|
FINISHED |
| Object | mass-produced |
—
|
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: mass-produced | Statement: [Packard V-1650, warProduction, mass-produced]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: warProduction Context triple: [Packard V-1650, warProduction, mass-produced]
-
A.
warDamage
Indicates damage that was caused as a direct consequence of war or armed conflict.
-
B.
hasMilitaryIndustry
Indicates that an entity possesses or is associated with an industry dedicated to the research, development, production, or maintenance of military equipment, technology, or services.
-
C.
worldWar
Indicates a large-scale armed conflict involving multiple nations across different regions of the world, typically encompassing numerous battles, alliances, and theaters of war.
-
D.
statusDuringWorldWarII
Indicates the role, condition, or classification an entity had specifically during the period of World War II.
-
E.
majorWar
Indicates a large-scale, intense armed conflict between major powers or involving substantial military forces and widespread impact.
- 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bdc0f8d08190b340012a9eb26275 |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5ed2b88190aab992913957e1cf |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bcc82e38819081c3615e1cc7a66f |
completed | March 1, 2026, 10:25 p.m. |
Created at: March 1, 2026, 7:46 p.m.