Triple
T15435984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael (The Good Place) |
E369762
|
entity |
| Predicate | goalAtStart |
P63932
|
FINISHED |
| Object | torture humans in an experimental neighborhood |
—
|
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: torture humans in an experimental neighborhood | Statement: [Michael (The Good Place), goalAtStart, torture humans in an experimental neighborhood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: goalAtStart Context triple: [Michael (The Good Place), goalAtStart, torture humans in an experimental neighborhood]
-
A.
initialGoal
chosen
Indicates that something represents the first or starting objective or target in a sequence of goals.
-
B.
goalIn
Indicates that one entity’s objective, aim, or intended outcome is located within, directed toward, or achieved inside another entity or context.
-
C.
goalNumber
Indicates that an entity is associated with a specific target or objective quantified as a number.
-
D.
goalType
Indicates the specific category or nature of a goal associated with an entity or action.
-
E.
laterGoal
Indicates that one goal occurs or is intended to be achieved after another goal in time.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03edb3ec481908b26164d4470c9bc |
completed | April 16, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69ded27f45548190a6d2b1b85cb47444 |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:21 a.m.