Triple
T12914107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vergeltungswaffe 2 |
E308931
|
entity |
| Predicate | numberFiredInCombat |
P23883
|
FINISHED |
| Object | over 3000 |
—
|
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: over 3000 | Statement: [Vergeltungswaffe 2, numberFiredInCombat, over 3000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberFiredInCombat Context triple: [Vergeltungswaffe 2, numberFiredInCombat, over 3000]
-
A.
numberLaunchedInCombat
Indicates the quantity of times an entity has been launched or deployed specifically in combat operations.
-
B.
numberOfShotsFired
chosen
Indicates the total count of shots that were discharged in the described event or action.
-
C.
timeInCombat
Indicates the duration that an entity spends engaged in combat or active fighting.
-
D.
sawCombat
Indicates that an entity directly participated in active military or armed conflict.
-
E.
hasCombat
Indicates that an entity engages in, is involved with, or possesses the capability for combat or fighting interactions with other entities.
- 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_69d7bdf92b588190acdf2a2291ac4590 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971a0d6508190bca9668e9e06abfe |
completed | April 10, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69d96fa9b7708190a9e9fa30f59ff580 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:41 p.m.