Triple
T438224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. National Monument |
E10056
|
entity |
| Predicate | firstExampleInception |
P61
|
FINISHED |
| Object | 1906 |
—
|
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: 1906 | Statement: [U.S. National Monument, firstExampleInception, 1906]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstExampleInception Context triple: [U.S. National Monument, firstExampleInception, 1906]
-
A.
inception
chosen
Indicates the point in time or event at which something begins, originates, or is first established.
-
B.
firstDemonstrated
Indicates that one entity was the earliest to show, prove, or exemplify a particular concept, method, or capability in relation to another entity or context.
-
C.
firstAppeared
Indicates the earliest known time or context in which an entity was introduced, observed, or came into existence.
-
D.
firstModel
Indicates that an entity is the initial or earliest model/version in a sequence or series of models.
-
E.
hasExample
Indicates that one entity serves as an instance, illustration, or concrete example 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_69a2e8465ef481909655c681b01e2986 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2ef283be881909444aaf257451747 |
completed | Feb. 28, 2026, 1:35 p.m. |
| PD | Predicate disambiguation | batch_69a2eddb98e081909efcf9f0a955a908 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.