Triple
T17101245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Lady in the Lake |
E414984
|
entity |
| Predicate | hasMurderMystery |
P124121
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [The Lady in the Lake, hasMurderMystery, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMurderMystery Context triple: [The Lady in the Lake, hasMurderMystery, yes]
-
A.
containsMurderMystery
chosen
Indicates that one entity (such as a work or collection) includes or features a murder mystery as part of its content.
-
B.
hasMystery
Indicates that one entity possesses, contains, or is associated with something unknown, secret, or unexplained in relation to another entity.
-
C.
hasMurderer
Indicates that one entity is the person who committed the murder of another entity.
-
D.
mysteryAssociatedWith
Indicates a relationship where something is connected to, involved in, or characterized by an element of mystery or the unknown.
-
E.
mysterySet
Indicates that an entity belongs to a collection or group whose nature, contents, or defining criteria are unknown or intentionally unspecified.
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc0182cc8190b8aa9c980f11ba57 |
completed | April 18, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69e35d6b1b988190a8d6b6fe78c35e59 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:35 a.m.