Triple
T6167957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Case of the Lucky Legs |
E137616
|
entity |
| Predicate | fictionalGenre |
P69182
|
FINISHED |
| Object | whodunit |
—
|
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: whodunit | Statement: [The Case of the Lucky Legs, fictionalGenre, whodunit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalGenre Context triple: [The Case of the Lucky Legs, fictionalGenre, whodunit]
-
A.
fictionalMedium
Indicates that a work of fiction is presented or conveyed through a particular medium or format (such as a book, film, game, or comic).
-
B.
fictionalOrigin
Indicates that one entity originates from, or was first introduced within, a fictional work, universe, or narrative created by another entity.
-
C.
fictionalMaterial
Indicates that something is made of, composed of, or incorporates a material that exists only in fiction or imagination.
-
D.
fictionalIndustry
Indicates that an entity operates within an industry or sector that exists only in fiction rather than in the real world.
-
E.
fictionalUse
Indicates that one entity makes use of another within a fictional or imaginary context, rather than in real-world usage.
- 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_69c008a68c508190a8d78245c865960e |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05d647ae48190a1db07b4f4a06e67 |
completed | March 22, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69c055f5b81481908819515cdc334ae6 |
completed | March 22, 2026, 8:49 p.m. |
| PDg | Predicate description generation | batch_69c056df95ac8190bc5efe050d3af864 |
completed | March 22, 2026, 8:53 p.m. |
Created at: March 22, 2026, 4:18 p.m.