Triple
T15929074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Tilton |
E386276
|
entity |
| Predicate | positionInScandal |
P29490
|
FINISHED |
| Object | central female figure |
—
|
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: central female figure | Statement: [Elizabeth Tilton, positionInScandal, central female figure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionInScandal Context triple: [Elizabeth Tilton, positionInScandal, central female figure]
-
A.
associatedScandal
chosen
Indicates a relationship where an entity is linked to, involved in, or notably connected with a particular scandal.
-
B.
positionOnCrime
Indicates a stance, opinion, or policy position that an entity holds regarding crime or crime-related issues.
-
C.
disgracedFor
Indicates that an entity has lost honor, respect, or status specifically because of the associated reason, action, or circumstance.
-
D.
positionInCase
Indicates the specific role, status, or placement that an entity holds within a particular case or legal proceeding.
-
E.
timeOfMajorScandal
Indicates the specific time period during which a major scandal involving the entity occurred.
- 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_69d86da750008190987eb26be3f6c118 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e172b48b308190bc430b2308cbc75b |
completed | April 16, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69e142cf5c548190a931f7b58144cd31 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:52 a.m.