Triple
T19587919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Travels in Arabia |
E470150
|
entity |
| Predicate | timePeriodOfContent |
P302
|
FINISHED |
| Object | early 19th century |
—
|
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: early 19th century | Statement: [Travels in Arabia, timePeriodOfContent, early 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timePeriodOfContent Context triple: [Travels in Arabia, timePeriodOfContent, early 19th century]
-
A.
timeSpanOfContentsStart
Indicates the point in time when the contents associated with something begin.
-
B.
timePeriod
chosen
Indicates the specific span or interval of time during which an event, state, or relationship occurs or is valid.
-
C.
timePeriodFormulated
Indicates the time period during which something (such as a concept, theory, or plan) was formulated or developed.
-
D.
typicalViewingTime
Indicates the usual or most common amount of time an entity is viewed or watched under normal circumstances.
-
E.
timePeriodCategory
Indicates the classification of a time period into a specific category or type (e.g., era, phase, or temporal grouping).
- 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e64052f61c81908bb49927d4246030 |
completed | April 20, 2026, 3:03 p.m. |
| PD | Predicate disambiguation | batch_69e514dbdb988190b55931a8138c73e7 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:43 p.m.