Triple
T5680450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harlequin |
E125185
|
entity |
| Predicate | typicalProp |
P5084
|
FINISHED |
| Object | slapstick |
—
|
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: slapstick | Statement: [Harlequin, typicalProp, slapstick]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalProp Context triple: [Harlequin, typicalProp, slapstick]
-
A.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
B.
typicalFeatures
chosen
Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
-
C.
usesProp
Indicates that one entity employs, utilizes, or makes use of a particular property, resource, or object in performing an action or fulfilling a function.
-
D.
typicalCoreType
Indicates that something is a standard or characteristic core type within a given classification or system.
-
E.
typicalKey
Indicates that the referenced key is the standard or most commonly used key associated with an entity or context.
- 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_69c0082a884c8190a79001bae658941f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0248751bc8190b12aaa42d1ef17e3 |
completed | March 22, 2026, 5:19 p.m. |
| PD | Predicate disambiguation | batch_69c021be59088190a81c880957f666ab |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:44 p.m.