Triple
T397154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Crossroads |
E9207
|
entity |
| Predicate | BakerYield |
P10952
|
FINISHED |
| Object | 23 kilotons of TNT |
—
|
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: 23 kilotons of TNT | Statement: [Operation Crossroads, BakerYield, 23 kilotons of TNT]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: BakerYield Context triple: [Operation Crossroads, BakerYield, 23 kilotons of TNT]
-
A.
estimatedTeaWeight
Indicates the quantified amount of tea that is approximated or predicted in weight rather than precisely measured.
-
B.
isCookedBy
Indicates that something has been prepared or made ready for eating through cooking by a particular agent.
-
C.
hasMainIngredient
Indicates that one entity is the primary or most significant ingredient used to make another entity.
-
D.
grain
Indicates that one entity is composed of or contains a granular substance or small particles of another entity.
-
E.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
- 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_69a2e8004cb88190b92ed1add6abf41a |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ec8a941081909a152fda0ce24a98 |
completed | Feb. 28, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69a2e96d17d08190878d3a68b17d51ca |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2ea4545608190898436c72e10f39d |
completed | Feb. 28, 2026, 1:14 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.