Triple
T769628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murder in the White House |
E16251
|
entity |
| Predicate | protagonistRole |
P8706
|
FINISHED |
| Object | amateur sleuth |
—
|
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: amateur sleuth | Statement: [Murder in the White House, protagonistRole, amateur sleuth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistRole Context triple: [Murder in the White House, protagonistRole, amateur sleuth]
-
A.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
B.
hasProtagonist
chosen
Indicates that a work of narrative has a main character who serves as its central focus or driving agent.
-
C.
protagonistNationality
Indicates the country or national identity to which the protagonist of a work is associated or belongs.
-
D.
roleInDialogue
Indicates that an entity participates in a dialogue with a specific conversational role (e.g., speaker, listener, moderator) relative to other participants.
-
E.
hasMainRole
Indicates that an entity holds the primary or most significant role in relation to another entity or 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_69a49369a0848190af883934cee3db4c |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a70376988190be2826259f5281ab |
completed | March 1, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69a4a508c42c8190850a0ac7844a3ea9 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.