Triple
T15492260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean Leonnec |
E378716
|
entity |
| Predicate | characterCreatedInYear |
P118460
|
FINISHED |
| Object | 1924 |
—
|
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: 1924 | Statement: [Jean Leonnec, characterCreatedInYear, 1924]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterCreatedInYear Context triple: [Jean Leonnec, characterCreatedInYear, 1924]
-
A.
characterPortrayedInYear
Indicates that a particular character was portrayed in a specific year.
-
B.
characterCreatedInCentury
Indicates that a fictional character was first created or introduced during a specified century.
-
C.
yearCast
Indicates the specific year in which a particular cast or casting of something (such as a film, show, or performance) took place.
-
D.
activeInFictionalYear
Indicates that an entity is active or operating during a specified fictional or imaginary year within a narrative or fictional timeline.
-
E.
wasNamedInYear
Indicates that an entity received or was given its name in a specific year.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fad723481908d2aa33e8f065f2f |
completed | April 16, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69ded2874b788190999158e0f043be21 |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded5deee00819099fa3e43313312e1 |
completed | April 15, 2026, 12:03 a.m. |
Created at: April 10, 2026, 3:49 a.m.