Triple
T33584455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark 39 nuclear bomb |
E860241
|
entity |
| Predicate | numberOfBombsInAccident |
P204146
|
FINISHED |
| Object | two |
—
|
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: two | Statement: [Mark 39 nuclear bomb, numberOfBombsInAccident, two]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfBombsInAccident Context triple: [Mark 39 nuclear bomb, numberOfBombsInAccident, two]
-
A.
resultOfBombing
Indicates that something exists or occurs as a consequence or outcome of a bombing event.
-
B.
numberOfExplosions
Indicates the count of distinct explosion events associated with an entity or situation.
-
C.
numberOfPeopleKilledInBombing
Indicates the total count of people who were killed as a direct result of a specific bombing event.
-
D.
numberOfFailedBombs
Indicates the count of bombs associated with an entity that did not successfully detonate or function as intended.
-
E.
numberOfBomberDeaths
Indicates the quantity of individuals who died while serving as bombers in a given context or event.
- 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_69f3497e70e48190951c94d072879bec |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a03352bb9688190b965d188769fcacd |
completed | May 12, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_6a033329ae5c81909532843fe716ec77 |
completed | May 12, 2026, 2:03 p.m. |
| PDg | Predicate description generation | batch_6a03352af3f881909f13f586214027ac |
completed | May 12, 2026, 2:11 p.m. |
Created at: May 1, 2026, 1:40 a.m.