Triple
T1108839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tin Lizzie |
E25545
|
entity |
| Predicate | associatedWithInnovation |
P14232
|
FINISHED |
| Object | moving assembly line production |
—
|
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: moving assembly line production | Statement: [Tin Lizzie, associatedWithInnovation, moving assembly line production]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithInnovation Context triple: [Tin Lizzie, associatedWithInnovation, moving assembly line production]
-
A.
innovation
Indicates the introduction or development of something new or significantly improved compared to existing methods, products, or ideas.
-
B.
innovationArea
Indicates the thematic or domain-specific field in which an innovation is focused or applied.
-
C.
associatedWithTechnology
Indicates a relationship where an entity is connected to, involved with, or utilizes a particular technology.
-
D.
hasInnovationHub
Indicates that an entity hosts, contains, or is associated with a dedicated center or facility focused on innovation activities.
-
E.
technologyPioneered
chosen
Indicates that an entity was the first or among the first to develop, introduce, or significantly advance a particular technology.
- 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_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. |
Created at: March 1, 2026, 7:43 p.m.