Triple
T34982239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krenim |
E1008844
|
entity |
| Predicate | chronitonTorpedoCountermeasure |
P59439
|
FINISHED |
| Object | temporal shielding |
—
|
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: temporal shielding | Statement: [Krenim, chronitonTorpedoCountermeasure, temporal shielding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chronitonTorpedoCountermeasure Context triple: [Krenim, chronitonTorpedoCountermeasure, temporal shielding]
-
A.
antiTorpedoProtection
chosen
Indicates a defensive relationship where measures are in place to protect against or mitigate the effects of torpedo attacks.
-
B.
tertiaryArmament
Indicates the relationship where an entity possesses or is equipped with a third-level (tertiary) weapon or armament beyond its primary and secondary armaments.
-
C.
numberOfTorpedoesFired
Indicates the quantity of torpedoes that have been launched or discharged in a given context or event.
-
D.
torpedoDamageEffect
Indicates the effect or impact that a torpedo’s damage has on its target.
-
E.
torpedoCaliber
Indicates the specific diameter or size classification of a torpedo used in a given context or system.
- 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_69f76dc844a48190881951fffb83d17e |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe0d165a48819098b854318a50d76c |
completed | May 8, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69fe0931002481908a95b34f95e9f64e |
completed | May 8, 2026, 4:02 p.m. |
Created at: May 3, 2026, 4:01 p.m.