Triple
T37705272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Patton |
E939180
|
entity |
| Predicate | hasTranslatedToLanguage |
P45244
|
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: [Paul Patton, hasTranslatedToLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTranslatedToLanguage Context triple: [Paul Patton, hasTranslatedToLanguage, English]
-
A.
hasTranslated
Indicates that one entity has rendered the content of another entity from one language into a different language.
-
B.
hasTranslatedFrom
Indicates that a work or text has been translated from a specified original language or source language.
-
C.
hasTranslation
Indicates that one entity is a translation or translated version of another entity in a different language.
-
D.
hasWorkTranslatedInto
chosen
Indicates that a work has been translated into a specified language or target work.
-
E.
hasTranslationEquivalent
Indicates that one expression in a given language corresponds in meaning to another expression in a different 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_69f76edb49dc8190b951dce9ce6ef789 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a004c41f13c8190bc47daf6a5ca3949 |
completed | May 10, 2026, 9:13 a.m. |
| PD | Predicate disambiguation | batch_6a004bce3e3081909b35ae5b3bf2b35e |
completed | May 10, 2026, 9:11 a.m. |
Created at: May 3, 2026, 4:18 p.m.