Triple
T28261860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Grande-Duchesse de Gérolstein |
E712602
|
entity |
| Predicate | revisedActCount |
P1039
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [La Grande-Duchesse de Gérolstein, revisedActCount, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: revisedActCount Context triple: [La Grande-Duchesse de Gérolstein, revisedActCount, 4]
-
A.
revisedActs
Indicates that one act is a modified, updated, or corrected version of another act.
-
B.
amendmentCount
chosen
Indicates the number of amendments that have been made to a given item, document, or entity.
-
C.
repealedAndReenacted
Indicates that an existing law or regulation was formally revoked and simultaneously replaced by a new version covering the same subject matter.
-
D.
revisedStatutesYear
Indicates the year in which a set of statutes or laws was revised or codified.
-
E.
latestSeriesOfAmendments
Indicates that one entity is the most recent set or version of amendments associated with 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_69efb5207eb08190827e4c34048030b1 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f64419e5f881908d08370af0445383 |
completed | May 2, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 11:12 p.m.