Triple
T15436003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael (The Good Place) |
E369762
|
entity |
| Predicate | notableObjectOfInterest |
P7672
|
FINISHED |
| Object | bow ties |
—
|
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: bow ties | Statement: [Michael (The Good Place), notableObjectOfInterest, bow ties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableObjectOfInterest Context triple: [Michael (The Good Place), notableObjectOfInterest, bow ties]
-
A.
notableObject
chosen
Indicates that an entity is especially significant, famous, or noteworthy as an object in a given context or domain.
-
B.
notableObjectOfStudy
Indicates that a subject is a significant or prominent focus of research, analysis, or scholarly attention for another entity.
-
C.
notableObjective
Indicates that an entity has a significant, distinguished, or widely recognized goal, purpose, or target associated with it.
-
D.
notableTarget
Indicates that the subject is particularly significant, prominent, or noteworthy with respect to the specified target.
-
E.
featureOfInterest
Indicates the entity or object that is the primary subject or focus of the described observation, measurement, or analysis.
- 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.