Triple
T1078684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcha Real |
E23896
|
entity |
| Predicate | earliestKnownUse |
P3921
|
FINISHED |
| Object | 18th 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: 18th century | Statement: [Marcha Real, earliestKnownUse, 18th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earliestKnownUse Context triple: [Marcha Real, earliestKnownUse, 18th century]
-
A.
languageOfEarliestForm
Indicates the language in which the earliest known form or attested version of something (e.g., a text, name, or expression) is recorded.
-
B.
locationOfEarlyUse
Indicates the place where something was first or among the earliest instances to be used or applied.
-
C.
firstClearlyAttestedIn
chosen
Indicates the earliest known point in time or source where something is clearly documented or evidenced.
-
D.
firstWidelyUsedFor
Indicates that something was the earliest instance to be broadly adopted or commonly used for a particular purpose or application.
-
E.
historicalPeriodOfUse
Indicates the time period during which something was in active use or commonly utilized.
- 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b943b41481909b24050ca7e78971 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b73d9f08819093668104f129840e |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.