Triple
T12670005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Q Who |
E302651
|
entity |
| Predicate | settingYearFictional |
P31557
|
FINISHED |
| Object | 2365 |
—
|
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: 2365 | Statement: [Q Who, settingYearFictional, 2365]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingYearFictional Context triple: [Q Who, settingYearFictional, 2365]
-
A.
setInFictionalYear
chosen
Indicates that the events or narrative of a work are situated in a specified fictional or non-real calendar year.
-
B.
fictionalBirthYear
Indicates the year in which a fictional character is stated or assumed to have been born within its narrative or canon.
-
C.
foundedInFictionalYear
Indicates that an entity was established or created in a year that exists only within a fictional or imaginary timeline, rather than in real-world history.
-
D.
fictionalAge
Indicates the age attributed to an entity within a fictional or narrative context, rather than its real-world age.
-
E.
basedOnFictionalDateIn
Indicates that something is derived from, inspired by, or determined using a fictional date occurring within a specified work, timeline, or fictional context.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960bb64ec8190bd0400cf0cc8b0a7 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:20 p.m.