Triple
T38011329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dickens's Dictionary of Paris |
E948370
|
entity |
| Predicate | publisherLanguageAudience |
P94660
|
FINISHED |
| Object | English-speaking readers |
—
|
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-speaking readers | Statement: [Dickens's Dictionary of Paris, publisherLanguageAudience, English-speaking readers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publisherLanguageAudience Context triple: [Dickens's Dictionary of Paris, publisherLanguageAudience, English-speaking readers]
-
A.
hasTargetAudienceLanguage
chosen
Indicates that something is intended for or directed toward an audience that speaks a particular language.
-
B.
publisherLanguageEdition
Indicates the specific language edition in which a publisher issues or has issued a work.
-
C.
primaryLanguageMarket
Indicates that a particular language is the main or dominant language used within a given market or market segment.
-
D.
targetsLanguage
Indicates that an action, resource, or entity is specifically directed toward, designed for, or intended to be used with a particular language.
-
E.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
- 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_69f76efb4b10819092c8c2ba28ac06a8 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a000efe971081909de03f875a7ad6cc |
completed | May 10, 2026, 4:52 a.m. |
| PD | Predicate disambiguation | batch_6a000c4ffe788190a5757af60aadd9f3 |
completed | May 10, 2026, 4:40 a.m. |
Created at: May 3, 2026, 4:20 p.m.