Triple
T33593126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yvonne Carmichael |
E860482
|
entity |
| Predicate | facesCharge |
P176944
|
FINISHED |
| Object | murder |
—
|
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: murder | Statement: [Yvonne Carmichael, facesCharge, murder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: facesCharge Context triple: [Yvonne Carmichael, facesCharge, murder]
-
A.
facesArea
Indicates that one entity is oriented toward, overlooks, or has its primary exposure directed toward a specified area.
-
B.
facesAssociatedWith
Indicates that there is a connection or linkage between certain faces (e.g., facial instances or representations) and related entities, contexts, or records.
-
C.
faceType
Indicates the specific shape or structural category of a face that an entity possesses or is characterized by.
-
D.
faceTransitivity
Indicates that a facing or orientation relationship between entities is preserved or carried through transitively across intermediate entities.
-
E.
facedBy
Indicates that one entity is oriented toward and directly opposite another entity, such that it is facing it.
- 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_69f3497e70e48190951c94d072879bec |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f8164698819090c1b471f1caa4c6 |
completed | May 3, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69f6f6632dfc8190af85e258c8519207 |
completed | May 3, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69f6f70b0ca081908b24a98937e6ef66 |
completed | May 3, 2026, 7:19 a.m. |
Created at: May 1, 2026, 1:40 a.m.