Triple
T269627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scorpion W2 |
E5601
|
entity |
| Predicate | designedToWorkIn |
P1129
|
FINISHED |
| Object | woodland environments |
—
|
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: woodland environments | Statement: [Scorpion W2, designedToWorkIn, woodland environments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designedToWorkIn Context triple: [Scorpion W2, designedToWorkIn, woodland environments]
-
A.
worksFor
Indicates that one entity is employed by or performs work on behalf of another entity, typically an organization or individual.
-
B.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
C.
appliesTo
chosen
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
-
D.
designedIn
Indicates that something was created, planned, or conceived during a particular time period or at a specific location.
-
E.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to 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_69a25853594c8190b05ec3a586ec88bf |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25db00ed48190be6f598807265356 |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b70d99c819085d8381a313a2a34 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:57 a.m.