Triple
T7674684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blockbusters |
E173831
|
entity |
| Predicate | questionClueType |
P78857
|
FINISHED |
| Object | answers begin with chosen letter |
—
|
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: answers begin with chosen letter | Statement: [Blockbusters, questionClueType, answers begin with chosen letter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: questionClueType Context triple: [Blockbusters, questionClueType, answers begin with chosen letter]
-
A.
questionType
Indicates the specific category or kind of question that an item, query, or prompt belongs to.
-
B.
puzzleType
Indicates the specific category or kind of puzzle that an item, activity, or problem belongs to.
-
C.
questionTopic
Indicates that a question is about, concerns, or is primarily focused on a particular topic or subject.
-
D.
seeType
Indicates that one entity observes, recognizes, or visually perceives another entity of a particular type or category.
-
E.
knowledgeType
Indicates the specific category or nature of knowledge associated with an entity or statement (e.g., factual, procedural, conceptual).
- 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_69c6995703e0819081de77361b602e78 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7048b0b448190889bd40e0a38e51a |
completed | March 27, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69c701618d3481908be84b76f36ac5a1 |
completed | March 27, 2026, 10:14 p.m. |
| PDg | Predicate description generation | batch_69c7048a01508190bc2e9ae8b863486c |
completed | March 27, 2026, 10:28 p.m. |
Created at: March 27, 2026, 4 p.m.