Triple
T35299745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heath Robinson machine |
E1019470
|
entity |
| Predicate | languageOfTargetTraffic |
P56541
|
FINISHED |
| Object | German |
—
|
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: German | Statement: [Heath Robinson machine, languageOfTargetTraffic, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfTargetTraffic Context triple: [Heath Robinson machine, languageOfTargetTraffic, German]
-
A.
targetsLanguage
Indicates that an action, resource, or entity is specifically directed toward, designed for, or intended to be used with a particular language.
-
B.
targetLanguage
chosen
Indicates the language that is the intended recipient or focus of a communication, translation, or linguistic operation.
-
C.
languageTargets
Indicates that a language is specifically directed at, intended for, or used to address a particular target entity (such as an audience, system, or domain).
-
D.
languageOfSurroundingCountry
Indicates that a language is the primary or commonly used language in the country surrounding a given place or region.
-
E.
languageOfEndpoints
Indicates that the related entities use or are associated with the same language at their respective endpoints in a communication or interaction.
- 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_69f76de7eedc8190a3bdc64ebbc05b42 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a00b7fb90f881908f73edf2be8cc3a5 |
completed | May 10, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_6a00b75593d08190b3e76191cd79cdec |
completed | May 10, 2026, 4:50 p.m. |
Created at: May 3, 2026, 4:03 p.m.