Triple
T26974150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Sims: Hot Date |
E679400
|
entity |
| Predicate | addsObjectType |
P161404
|
FINISHED |
| Object | phone-based taxi to downtown |
—
|
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: phone-based taxi to downtown | Statement: [The Sims: Hot Date, addsObjectType, phone-based taxi to downtown]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addsObjectType Context triple: [The Sims: Hot Date, addsObjectType, phone-based taxi to downtown]
-
A.
addsObjectType
chosen
Indicates that an entity introduces or includes a specific type of object into a collection, structure, or context.
-
B.
registerType
Indicates that an entity is classified or recorded under a specific type or category within a registration system.
-
C.
typicalObjectType
Indicates that something is a common or characteristic type of object typically associated with or involved in another entity or situation.
-
D.
addsFeatureType
Indicates that one entity introduces or incorporates a specific feature type into another entity or system.
-
E.
addsClass
Indicates that one entity introduces or appends a class (such as a classification, type, or code) to another entity.
- 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_69eeeb507a7081909d516e1fa08b7d29 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f625411c14819086492062e86ba8d5 |
completed | May 2, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69f623a91b9c8190b2e2fdbc55cb89b6 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 27, 2026, 6:41 a.m.