Triple
T3911788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth (Gentleman's Agreement) |
E87337
|
entity |
| Predicate | topicOfWorkAppearedIn |
P7040
|
FINISHED |
| Object | antisemitism |
—
|
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: antisemitism | Statement: [Elizabeth (Gentleman's Agreement), topicOfWorkAppearedIn, antisemitism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topicOfWorkAppearedIn Context triple: [Elizabeth (Gentleman's Agreement), topicOfWorkAppearedIn, antisemitism]
-
A.
subjectOfWork
chosen
Indicates that one entity is the main topic, focus, or theme that a particular work (such as a book, article, or artwork) is about.
-
B.
platformOfWorkAppearingIn
Indicates the platform or medium on which a given work is presented, published, or made available.
-
C.
fieldOfWork
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
-
D.
researchTopic
Indicates that a subject conducts or focuses research on a particular topic or area of study.
-
E.
topicOfAcademicCollaboration
Indicates that the entities are partners in a shared academic research or scholarly collaboration.
- 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_69aed9424514819086e9c58adde6652d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee75eedcc81908088ff4dbb8be56b |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:22 p.m.