Triple
T9999969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Cal Lightman |
E197298
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object | Samuel Baum |
E215423
|
NE 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: Samuel Baum | Statement: [Dr. Cal Lightman, createdBy, Samuel Baum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samuel Baum Context triple: [Dr. Cal Lightman, createdBy, Samuel Baum]
-
A.
Samuel Baum
chosen
Samuel Baum is a television writer and producer best known for creating the crime drama series "Lie to Me."
-
B.
Samuel Blum
Samuel Blum is a relatively obscure individual whose specific notability is not clearly established from the given information.
-
C.
Samuel Diescher
Samuel Diescher was a prominent 19th-century civil and mechanical engineer known for designing several American inclines and industrial structures, particularly in Pittsburgh.
-
D.
Samuel Weiss
Samuel Weiss is a relatively obscure individual whose specific public significance is not clearly established from the available information.
-
E.
Samuel Lapp
Samuel Lapp is a young Amish boy in the film "Witness," whose accidental observation of a murder drives the story’s central conflict.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca82f3b61c81908ecc2c1c96dbc2e4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdcc8dc9c081909b6d20909ada09cf |
completed | April 2, 2026, 1:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d94ae0a9608190ab241b6a62fe807b |
completed | April 10, 2026, 7:09 p.m. |
Created at: March 30, 2026, 8:51 p.m.