Triple
T16560284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | K6 red telephone kiosk |
E402318
|
entity |
| Predicate | widespreadBy |
P2899
|
FINISHED |
| Object | late 1930s |
—
|
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: late 1930s | Statement: [K6 red telephone kiosk, widespreadBy, late 1930s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: widespreadBy Context triple: [K6 red telephone kiosk, widespreadBy, late 1930s]
-
A.
widelyCoveredBy
Indicates that something (such as an event, topic, or issue) receives extensive attention or reporting from many media outlets or information sources.
-
B.
isWidelyUsed
Indicates that something is commonly or extensively utilized across many contexts, users, or situations.
-
C.
widerUsage
Indicates that one entity is used or applied more broadly, frequently, or in a greater variety of contexts than another.
-
D.
spreadBy
chosen
Indicates that something is transmitted, dispersed, or propagated through the agency or action of a specified entity or medium.
-
E.
isWidelyKnown
Indicates that something is generally recognized or familiar to a large number of people.
- 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_69d8838648088190acf97ef11fc3f61b |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3576d88288190b33543bea4706a36 |
completed | April 18, 2026, 10:05 a.m. |
| PD | Predicate disambiguation | batch_69e296a47b7481909d9958158510c806 |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:15 a.m.