Triple
T10260779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Marley |
E240587
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Faces |
E265073
|
NE 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: Faces | Statement: [John Marley, notableWork, Faces]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Faces Context triple: [John Marley, notableWork, Faces]
-
A.
Faces
chosen
Faces is a 1968 independent drama film written and directed by John Cassavetes, noted for its raw, improvisational style and intense exploration of marital breakdown and human relationships.
-
B.
Faces
Faces is a critically acclaimed 2014 mixtape by American rapper Mac Miller, known for its introspective lyrics, experimental production, and exploration of themes like addiction and mental health.
-
C.
Faces
Faces was a British rock band formed in 1969, known for its bluesy, hard rock sound and energetic live performances.
-
D.
Heads, Features and Faces
Heads, Features and Faces is an instructional art book by George Bridgman that teaches artists how to construct and draw the human head and facial features with an emphasis on structure and anatomy.
-
E.
Azure Face API
Azure Face API is a cloud-based facial recognition and analysis service from Microsoft that detects, identifies, and analyzes human faces in images.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d25bc7f88190b7e83243894d1aeb |
completed | April 7, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f7f1500c819089d569dbfce705b8 |
completed | April 9, 2026, 12:50 a.m. |
Created at: April 6, 2026, 11:32 a.m.