Triple
T5656228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julie |
E124624
|
entity |
| Predicate | firstRecordedUse |
P55558
|
FINISHED |
| Object | medieval Europe as a form of Julia |
—
|
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: medieval Europe as a form of Julia | Statement: [Julie, firstRecordedUse, medieval Europe as a form of Julia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstRecordedUse Context triple: [Julie, firstRecordedUse, medieval Europe as a form of Julia]
-
A.
firstHistoricalUse
Indicates that the subject entity represents the earliest known or recorded instance of the object entity being used or occurring in history.
-
B.
historicalPeriodOfFirstUse
chosen
Indicates the historical time period during which something was first used or came into use.
-
C.
firstClearlyAttestedIn
Indicates the earliest known point in time or source where something is clearly documented or evidenced.
-
D.
firstRecordingDate
Indicates the date on which an entity’s first recording (e.g., audio, video, or similar captured performance) was made.
-
E.
firstOfficialUse
Indicates the earliest point in time when something was formally or officially put into use.
- 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_69c0082774a481909d7e63fb2aad56ac |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c0236d3f94819095111c41a323612d |
completed | March 22, 2026, 5:14 p.m. |
| PD | Predicate disambiguation | batch_69c021ba4ec481909db8cdbf0e907dd6 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:42 p.m.