Triple
T984667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Get Happy |
E21251
|
entity |
| Predicate | associatedCostumeInSummerStock |
P21953
|
FINISHED |
| Object | black fedora |
—
|
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: black fedora | Statement: [Get Happy, associatedCostumeInSummerStock, black fedora]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedCostumeInSummerStock Context triple: [Get Happy, associatedCostumeInSummerStock, black fedora]
-
A.
costumeType
Indicates the specific kind or category of costume associated with an entity.
-
B.
originalCostumeColor
Indicates the color that a costume originally had before any changes, damage, or alterations.
-
C.
summerBase
Indicates a base or location where an entity is situated or operates specifically during the summer season.
-
D.
haveDistinctCostume
Indicates that the entities each possess a costume that is different from the others’ costumes.
-
E.
hasSeasonalStatus
Indicates that an entity’s status, availability, or condition varies according to a particular season or time of year.
- 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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4959fe48190a78bd811cbc888ab |
completed | March 1, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69a4b2aa219081908a6b0ef786b4aa52 |
completed | March 1, 2026, 9:42 p.m. |
| PDg | Predicate description generation | batch_69a4b345f890819092b51bf8128da461 |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:41 p.m.