Triple
T3171289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theme from "A Connecticut Yankee" (musical) |
E66350
|
entity |
| Predicate | originalProductionYear |
P10580
|
FINISHED |
| Object | 1927 |
—
|
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: 1927 | Statement: [Theme from "A Connecticut Yankee" (musical), originalProductionYear, 1927]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalProductionYear Context triple: [Theme from "A Connecticut Yankee" (musical), originalProductionYear, 1927]
-
A.
firstProductionYear
Indicates the year in which something (such as a product, work, or item) was first produced.
-
B.
originYear
Indicates the year in which something first originated, was created, or began.
-
C.
modelProduced
Indicates that a particular model has generated or produced a specified output, result, or artifact.
-
D.
productionStartYear
Indicates the year in which the production of an item, work, or entity first began.
-
E.
compositionYear
chosen
Indicates the year in which a work (such as a piece of music, art, or literature) was originally created or composed.
- 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_69ad8585d7988190af37365331093ccd |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada66c043081908eb23a4fe3420a78 |
completed | March 8, 2026, 4:40 p.m. |
| PD | Predicate disambiguation | batch_69ad9e0076b4819094628f1ad10b8f68 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:06 p.m.