Triple
T6167928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Case of the Howling Dog |
E137615
|
entity |
| Predicate | hasCourtroomScenes |
P69181
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [The Case of the Howling Dog, hasCourtroomScenes, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCourtroomScenes Context triple: [The Case of the Howling Dog, hasCourtroomScenes, true]
-
A.
courtroom
Indicates a relationship where a legal proceeding or judicial action takes place within or is associated with a specific courtroom.
-
B.
appearsInCourt
Indicates that an entity is formally present and participating in a legal proceeding before a court.
-
C.
hasCourts
Indicates that an entity possesses, contains, or is equipped with one or more courts (e.g., legal, sports, or judicial facilities).
-
D.
hasCourtInEach
Indicates that an entity possesses or maintains a court in every member of a specified set of locations or jurisdictions.
-
E.
hasTribunal
Indicates that an entity is associated with or subject to a specific tribunal, such as a court or adjudicative body, that has authority over its cases or matters.
- 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.