Triple
T1108827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tin Lizzie |
E25545
|
entity |
| Predicate | associatedWithBodyStyles |
P23419
|
FINISHED |
| Object | touring car |
—
|
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: touring car | Statement: [Tin Lizzie, associatedWithBodyStyles, touring car]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithBodyStyles Context triple: [Tin Lizzie, associatedWithBodyStyles, touring car]
-
A.
associatedBody
Indicates a relationship where one entity is linked or connected to another entity as its related or corresponding body.
-
B.
belongsToBody
Indicates that something is a part of, or under the ownership/authority of, a particular body or organization.
-
C.
relatedStyle
Indicates that one style is associated with, similar to, or derived from another style in some relevant way.
-
D.
usedWithStyle
Indicates that something is employed or applied in conjunction with a particular style or stylistic manner.
-
E.
associatedWithText
Indicates that an entity has a contextual or semantic connection to a specific piece of text.
- 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_69a49428d4448190b3b36991ceae87ce |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9e6134481909f348986a25f65c6 |
completed | March 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69a4b749e2a881909ef28745a7d2d917 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7bd3d50819091e6f1d2ffe4c7ee |
completed | March 1, 2026, 10:03 p.m. |
Created at: March 1, 2026, 7:43 p.m.