Triple
T2462432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fordism |
E54561
|
entity |
| Predicate | emergedInIndustry |
P40664
|
FINISHED |
| Object | automobile industry |
—
|
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: automobile industry | Statement: [Fordism, emergedInIndustry, automobile industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emergedInIndustry Context triple: [Fordism, emergedInIndustry, automobile industry]
-
A.
foundingIndustry
Indicates the industry or sector in which an entity was originally founded or began its primary operations.
-
B.
usedInIndustry
Indicates that something is employed or applied within a particular industry or industrial sector.
-
C.
emergedWith
Indicates that one entity came forth, appeared, or became visible at the same time and in association with another entity.
-
D.
emergedFrom
Indicates that one entity originated, arose, or came forth from another entity or source.
-
E.
emergedAround
Indicates that something came into existence or became noticeable at approximately a particular time or period.
- 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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd49c5aa081909ab4f726a458b77f |
completed | March 7, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69abd0b199488190aa381b36593ae1ac |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd49b5d2481908817aeb171e2bd61 |
completed | March 7, 2026, 7:32 a.m. |
Created at: March 6, 2026, 9:44 p.m.