Triple
T2033567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upkeep bouncing bomb |
E44570
|
entity |
| Predicate | explosiveMass |
P25889
|
FINISHED |
| Object | approximately 6,600 pounds of Torpex |
—
|
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: approximately 6,600 pounds of Torpex | Statement: [Upkeep bouncing bomb, explosiveMass, approximately 6,600 pounds of Torpex]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: explosiveMass Context triple: [Upkeep bouncing bomb, explosiveMass, approximately 6,600 pounds of Torpex]
-
A.
explosiveMaterialUsed
Indicates that an explosive material was employed or involved in carrying out a particular action or event.
-
B.
explosiveYieldApprox
chosen
Indicates that one entity has an approximate explosive yield value, typically expressing the estimated magnitude of an explosion or explosive device.
-
C.
explosiveDevice
Indicates the presence or involvement of an object designed to explode or cause an explosion in relation to the associated entities.
-
D.
explosiveLensType
Indicates the specific design or configuration of the explosive lens used to shape and direct the detonation wave.
-
E.
numberOfExplosions
Indicates the count of distinct explosion events associated with an entity or situation.
- 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_69a889144f2481909932f0746a93023d |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb93255248190bd47a54a7b3c7447 |
completed | March 7, 2026, 5:35 a.m. |
| PD | Predicate disambiguation | batch_69abb7a8125881909c0cb58b777c1faa |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:39 p.m.