Triple
T16526053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Last Bus to Woodstock |
E401439
|
entity |
| Predicate | adaptedLanguage |
P121206
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Last Bus to Woodstock, adaptedLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adaptedLanguage Context triple: [Last Bus to Woodstock, adaptedLanguage, English]
-
A.
adaptedInLanguage
chosen
Indicates that a work or content has been modified or translated so it can be presented or understood in a specified language.
-
B.
adoptedLanguage
Indicates that an entity has chosen and begun using a particular language, typically as its official, primary, or preferred means of communication.
-
C.
suffixLanguage
Indicates that one language is used as a suffix or ending element in the formation or representation of another language or linguistic expression.
-
D.
workLanguageVariant
Indicates that one language variant of a work is related to another version of the same work, typically differing by language or localization.
-
E.
languageAffected
Indicates that one entity has an impact on, modifies, or influences the characteristics, usage, or status of a language.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32ed3f0388190a9f03473c37dfc46 |
completed | April 18, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69e296995d388190b88ebe189dce890d |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:14 a.m.