Triple
T15039511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Revisionist History |
E378561
|
entity |
| Predicate | hasNotableEpisodeTopic |
P82948
|
FINISHED |
| Object | education reform |
—
|
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: education reform | Statement: [Revisionist History, hasNotableEpisodeTopic, education reform]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableEpisodeTopic Context triple: [Revisionist History, hasNotableEpisodeTopic, education reform]
-
A.
notableEpisodeTopics
chosen
Indicates that there is a notable or significant topic discussed in a particular episode.
-
B.
hasEpisodeAbout
Indicates that a particular episode (such as of a show, podcast, or series) focuses on, discusses, or is centered around a specified subject or topic.
-
C.
hasNotableSubject
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
-
D.
hasNotableShow
Indicates that an entity is associated with a particular show that is considered notable or significant.
-
E.
notableEpisode
Indicates that a particular episode is especially significant, memorable, or noteworthy in relation to the subject.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded82e79a481908ddb9609af8c4407 |
completed | April 15, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69de9a69d7848190b2b4662dd30f20e9 |
completed | April 14, 2026, 7:50 p.m. |
Created at: April 10, 2026, 3 a.m.