Triple
T18704044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leverage Consulting & Associates |
E457325
|
entity |
| Predicate | roleOfSophieDevereaux |
P39941
|
FINISHED |
| Object | grifter |
—
|
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: grifter | Statement: [Leverage Consulting & Associates, roleOfSophieDevereaux, grifter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleOfSophieDevereaux Context triple: [Leverage Consulting & Associates, roleOfSophieDevereaux, grifter]
-
A.
relationshipToSophie
chosen
Indicates the specific type of personal or social connection that an entity has to Sophie.
-
B.
roleInSherlock
Indicates the specific role or character that an entity portrays or holds in the context of the Sherlock series or franchise.
-
C.
roleInFrancesHa
Indicates that one entity plays a specific role or character in the film "Frances Ha" in relation to another entity.
-
D.
roleOfDianeSimmons
Indicates that an entity holds the role, position, or function associated with Diane Simmons.
-
E.
roleInSOFIA
Indicates the specific role or capacity an entity holds within the context of the SOFIA framework, project, or system.
- 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5671597ac819093dbb53553130f1e |
completed | April 19, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69e478de85088190ba5f005f1d39f587 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:49 a.m.