Triple
T34669183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | B-Spec |
E890331
|
entity |
| Predicate | A-SpecRelation |
P84787
|
FINISHED |
| Object | direct driving counterpart |
—
|
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: direct driving counterpart | Statement: [B-Spec, A-SpecRelation, direct driving counterpart]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: A-SpecRelation Context triple: [B-Spec, A-SpecRelation, direct driving counterpart]
-
A.
allyRelation
Indicates a cooperative, supportive relationship in which the entities act as allies toward shared or aligned goals.
-
B.
subjectRelation
chosen
Indicates that one entity stands in a specified relational role or connection to another entity.
-
C.
datumRelation
Indicates a relationship where one piece of data is connected to, derived from, or otherwise associated with another piece of data.
-
D.
symbolicRelation
Indicates a relationship where one entity stands for, represents, or conveys meaning about another through symbols or abstract signs.
-
E.
semanticRelation
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
- 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_69f349d9c59481908b36baa0be093aea |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f722fa31248190a1c9081ce8cfa37b |
completed | May 3, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_69f72157af108190880317a62e634bb0 |
completed | May 3, 2026, 10:20 a.m. |
Created at: May 1, 2026, 2:05 a.m.