Triple
T36120369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pagoda |
E1044725
|
entity |
| Predicate | appliesToModelSeries |
P39689
|
FINISHED |
| Object | Mercedes-Benz W113 SL |
—
|
NE NERFINISHED |
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: Mercedes-Benz W113 SL | Statement: [Pagoda, appliesToModelSeries, Mercedes-Benz W113 SL]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToModelSeries Context triple: [Pagoda, appliesToModelSeries, Mercedes-Benz W113 SL]
-
A.
hasModelSeries
chosen
Indicates a relationship where an item or product is associated with a specific model series it belongs to.
-
B.
connectsToSeries
Indicates that one entity is linked or associated with a particular series, establishing a connection or membership relationship between them.
-
C.
appliedInModel
Indicates that something (such as a method, technique, or concept) is used or implemented within a particular model.
-
D.
appliesTo
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
-
E.
appliesModel
Indicates that one entity uses or executes a specific model on another entity or data set.
- 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_69f76e356c908190abc6ca1e6a05b011 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff63e6b61081909c648bf0ff279481 |
completed | May 9, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69ff6381867881908ae0545df4b71df5 |
completed | May 9, 2026, 4:40 p.m. |
Created at: May 3, 2026, 4:08 p.m.