Triple
T12326391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madama Butterfly |
E293840
|
entity |
| Predicate | revisedVersionActCount |
P12050
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Madama Butterfly, revisedVersionActCount, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: revisedVersionActCount Context triple: [Madama Butterfly, revisedVersionActCount, 2]
-
A.
amendmentCount
Indicates the number of amendments that have been made to a given item, document, or entity.
-
B.
numberOfMajorRevisions
Indicates the count of significant revision events that have occurred for an entity.
-
C.
alternativeCounting
Indicates that there exists another valid way of counting or enumerating the same set of items or events, distinct from the primary counting method.
-
D.
amendedMultipleTimes
Indicates that the referenced item has undergone more than one formal amendment or modification over time.
-
E.
numberOfActs
chosen
Indicates the total count of discrete acts or actions associated with a given entity or event.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ec5be788190b82d2edc6a0f1095 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.