Triple
T36729695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Songbird |
E907294
|
entity |
| Predicate | formerCriminalName |
P202707
|
FINISHED |
| Object | Screaming Mimi |
—
|
NE NERFINISHED |
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: Screaming Mimi | Statement: [Songbird, formerCriminalName, Screaming Mimi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerCriminalName Context triple: [Songbird, formerCriminalName, Screaming Mimi]
-
A.
formerName
Indicates that an entity was previously known by a different name in the past.
-
B.
formerMemberName
Indicates that the referenced name belongs to an entity that was previously a member of a particular group, organization, or body but is no longer one.
-
C.
prisonerName
Indicates that a particular name is the official or recorded name of a given prisoner.
-
D.
accusedName
Indicates that a particular person or entity is identified as the one who is accused in an accusation or legal charge.
-
E.
hasFormerInmate
Indicates that an entity previously housed or supervised an individual who was once an inmate there.
- 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_69f76e746e4c8190a0d05cc6d57a643e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a00ae638fcc819096537b2c21366161 |
completed | May 10, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_6a00ae0551988190bcb3564ed9af2847 |
completed | May 10, 2026, 4:10 p.m. |
| PDg | Predicate description generation | batch_6a00ae622d9c81909815b10ed11cddfe |
completed | May 10, 2026, 4:12 p.m. |
Created at: May 3, 2026, 4:12 p.m.