Triple
T21959116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Max Liron Bratman |
E542274
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Bratman |
—
|
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: Bratman | Statement: [Max Liron Bratman, familyName, Bratman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bratman Context triple: [Max Liron Bratman, familyName, Bratman]
-
A.
Bratman
chosen
Bratman is a surname most notably associated with Jordan Bratman, an American music producer and former husband of singer Christina Aguilera.
-
B.
Brooks
Brooks is a small city in southeastern Alberta, Canada, known for its agricultural industry and role as a regional service and transportation hub.
-
C.
Brooks
Brooks is a common English-language surname borne by numerous notable individuals across politics, arts, sports, and other fields.
-
D.
Bikeman
Bikeman is a small coral atoll in the Southern Gilbert Islands of Kiribati, known for having largely submerged due to sea-level rise and coastal erosion.
-
E.
Mnookin
Mnookin is a surname most prominently associated with Jennifer L. Mnookin, an American legal scholar and university leader.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c47fab1081908dc74a6545dbb051 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1244204f081909742d4fe138610d6 |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 8 p.m.