Triple
T10559014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haris Zambarloukos |
E249163
|
entity |
| Predicate | roleInMurderOnTheOrientExpress |
P94674
|
FINISHED |
| Object | cinematographer |
—
|
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: cinematographer | Statement: [Haris Zambarloukos, roleInMurderOnTheOrientExpress, cinematographer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInMurderOnTheOrientExpress Context triple: [Haris Zambarloukos, roleInMurderOnTheOrientExpress, cinematographer]
-
A.
roleInSherlock
Indicates the specific role or character that an entity portrays or holds in the context of the Sherlock series or franchise.
-
B.
questionedCharacter
Indicates that one entity directed questions or an interrogation toward another entity.
-
C.
murderedIn
Indicates that one entity unlawfully killed another entity at or within a specified location.
-
D.
accusedCharacterPortrayedBy
Indicates that a particular actor or performer plays the role of the character who is accused within a given work.
-
E.
reasonForMurder
Indicates the motive or underlying cause that led someone to commit a murder.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5271e65688190bcf7931373d87f94 |
completed | April 7, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69d518fa0b4081909bffc936d78bd77b |
completed | April 7, 2026, 2:47 p.m. |
| PDg | Predicate description generation | batch_69d5270eca0481908573b698390c5b08 |
completed | April 7, 2026, 3:47 p.m. |
Created at: April 6, 2026, 12:35 p.m.