Triple
T12669256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Enterprise-D |
E302632
|
entity |
| Predicate | saucerSectionStatusAfterDestruction |
P56983
|
FINISHED |
| Object | crash-landed on Veridian III |
—
|
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: crash-landed on Veridian III | Statement: [USS Enterprise-D, saucerSectionStatusAfterDestruction, crash-landed on Veridian III]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: saucerSectionStatusAfterDestruction Context triple: [USS Enterprise-D, saucerSectionStatusAfterDestruction, crash-landed on Veridian III]
-
A.
destructionStatus
Indicates the condition or extent to which something has been damaged, ruined, or rendered unusable.
-
B.
afterDestruction
chosen
Indicates that one event, state, or condition occurs subsequent to and as a result of a prior act of destruction.
-
C.
destroyedDuring
Indicates that one entity was destroyed in the course of, or as a consequence of, a specified event or time period.
-
D.
demolitionStatus
Indicates the current state or progress of a demolition process affecting an entity.
-
E.
sufferedDestructionOf
Indicates that one entity experienced damage, ruin, or loss as a result of the destruction of another entity.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960bb64ec8190bd0400cf0cc8b0a7 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:20 p.m.