Triple
T18323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Containment |
E362
|
entity |
| Predicate | firstArticulatedIn |
P1416
|
FINISHED |
| Object | 1946 |
—
|
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: 1946 | Statement: [Containment, firstArticulatedIn, 1946]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstArticulatedIn Context triple: [Containment, firstArticulatedIn, 1946]
-
A.
firstOccupiedBy
Indicates which entity was the initial or earliest known occupant of a given place, position, or resource.
-
B.
isArtificial
Indicates that an entity is man-made or produced by human design rather than occurring naturally.
-
C.
firstCelebratedInYear
Indicates the year in which something (such as an event, holiday, or celebration) was first observed or celebrated.
-
D.
firstAwarded
Indicates the time or occasion when an award, honor, or recognition was given for the very first time.
-
E.
introduced
Indicates that one entity caused another entity to become known, presented, or brought into use for the first time to a person, group, or context.
- F. None of above. chosen
Provenance (4 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a246cbca108190a92478df126d9bf8 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a2464f61648190ac690044be194972 |
completed | Feb. 28, 2026, 1:35 a.m. |
| PDg | Predicate description generation | batch_69a246cb2904819085c13207565a1db2 |
completed | Feb. 28, 2026, 1:37 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.