Triple
T18066504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Hitchcock |
E432307
|
entity |
| Predicate | skillLevelAsDetective |
P129684
|
FINISHED |
| Object | incompetent |
—
|
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: incompetent | Statement: [Michael Hitchcock, skillLevelAsDetective, incompetent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skillLevelAsDetective Context triple: [Michael Hitchcock, skillLevelAsDetective, incompetent]
-
A.
detectiveType
Indicates that one entity is classified as a particular type or category of detective in relation to another entity.
-
B.
hasClericalDetective
Indicates that an entity includes or is associated with a detective who is also a member of the clergy.
-
C.
featuresPrivateDetective
Indicates that the subject includes or involves a private detective as a notable element or character.
-
D.
roleInSherlock
Indicates the specific role or character that an entity portrays or holds in the context of the Sherlock series or franchise.
-
E.
featuresDetectiveDuo
Indicates that the subject involves or centers around a pair of detectives working together as a team.
- 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4cce97ce08190a2f8762ce545e091 |
completed | April 19, 2026, 12:39 p.m. |
| PD | Predicate disambiguation | batch_69e3f90c652481908133a73106d78919 |
completed | April 18, 2026, 9:35 p.m. |
| PDg | Predicate description generation | batch_69e42d8eefa88190a700c7c1b4213e46 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:26 a.m.