Triple
T22957383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Walk Among the Tombstones |
E570796
|
entity |
| Predicate | hasUnlicensedPrivateInvestigatorProtagonist |
P141168
|
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: [A Walk Among the Tombstones, hasUnlicensedPrivateInvestigatorProtagonist, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnlicensedPrivateInvestigatorProtagonist Context triple: [A Walk Among the Tombstones, hasUnlicensedPrivateInvestigatorProtagonist, true]
-
A.
hasClericalDetective
Indicates that an entity includes or is associated with a detective who is also a member of the clergy.
-
B.
privateInvestigatorCharacter
chosen
Indicates that one entity is a character whose role or occupation is that of a private investigator in relation to the work or context specified by the other entity.
-
C.
hasFictionalDetective
Indicates that one entity (typically a work or series) features or includes a fictional detective character as part of its content.
-
D.
hasThiefCharacter
Indicates that an entity includes or features a character whose role or identity is that of a thief.
-
E.
hasInspectorProtagonist
Indicates that the main character in the work serves in the role of an inspector.
- 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_69e245b212a88190b5259caf51606084 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181f21e588190a5a88a15c1b55dea |
completed | April 29, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69ef3b882e708190b0eb0c87021c75b8 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:47 p.m.