Triple
T929847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Cross emblem |
E20064
|
entity |
| Predicate | commonlySeenOn |
P11801
|
FINISHED |
| Object | ambulances |
—
|
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: ambulances | Statement: [Red Cross emblem, commonlySeenOn, ambulances]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonlySeenOn Context triple: [Red Cross emblem, commonlySeenOn, ambulances]
-
A.
bestSeenIn
Indicates that something is most effectively or appropriately experienced, observed, or appreciated within a particular context, medium, or setting.
-
B.
widelyUsedIn
chosen
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
-
C.
alsoObservedOn
Indicates that the same entity, event, or phenomenon was additionally observed on another occasion, date, or context beyond the primary one referenced.
-
D.
someSpeciesAre
Indicates that at least one member of a specified group or category belongs to, or can be classified as, a particular species.
-
E.
alsoUsedIn
Indicates that something is additionally employed, applied, or present in another context, setting, or use case beyond the primary one.
- 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_69a493af3dc48190adb7263e6e445ea1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b349b3d0819090c58b4fb60c6a1b |
completed | March 1, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69a4b29876348190a29f4ff9878074a5 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.