Triple
T25655808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeremy Saunders |
E643230
|
entity |
| Predicate | fictionalUniverseLanguage |
P164802
|
FINISHED |
| Object | Bengali publications |
—
|
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: Bengali publications | Statement: [Jeremy Saunders, fictionalUniverseLanguage, Bengali publications]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalUniverseLanguage Context triple: [Jeremy Saunders, fictionalUniverseLanguage, Bengali publications]
-
A.
languageOfFictionalUniverse
Indicates the language used or spoken within a fictional universe or setting.
-
B.
fictionalUniverse
Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
-
C.
hasLanguageInUniverse
Indicates that a particular language exists or is used within a specified fictional or conceptual universe.
-
D.
hasFictionalUniverseProperty
Indicates that a fictional universe possesses a specific characteristic, attribute, or property.
-
E.
fictionalLanguage
Indicates a relationship where an entity uses, is expressed in, or is associated with a language that is invented or does not exist in reality.
- F. None of above. chosen
Provenance (4 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_69e77e7d8a848190a98d0162325fd780 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f650fc44e48190bc0e0a935eac62a6 |
completed | May 2, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69f64cab1f648190a2a9460690d18a37 |
completed | May 2, 2026, 7:12 p.m. |
| PDg | Predicate description generation | batch_69f650c466b881908954e43bfebae8a4 |
completed | May 2, 2026, 7:30 p.m. |
Created at: April 21, 2026, 6:32 p.m.