Triple
T16027592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oshkosh, Wisconsin |
E388756
|
entity |
| Predicate | historicallyKnownForIndustry |
P3008
|
FINISHED |
| Object | lumber 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: lumber industry | Statement: [Oshkosh, Wisconsin, historicallyKnownForIndustry, lumber industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicallyKnownForIndustry Context triple: [Oshkosh, Wisconsin, historicallyKnownForIndustry, lumber industry]
-
A.
hasHistoricIndustry
chosen
Indicates that an entity has been associated with a notable or historically significant industry or industrial activity in the past.
-
B.
traditionallyKnownFor
Indicates that something is widely and historically recognized or reputed for a particular characteristic, activity, product, or role.
-
C.
foundingIndustry
Indicates the industry or sector in which an entity was originally founded or began its primary operations.
-
D.
notableIndustry
Indicates that an entity is significantly recognized or prominent within a specified industry or sector.
-
E.
hasIndustrialHeritage
Indicates that an entity possesses or is associated with historically significant industrial sites, structures, or practices.
- 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_69d86dada3808190825d5f80d72fbe88 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1858a00888190b8505071575dc56f |
completed | April 17, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e1826a4f7c8190aba6d4f1075141b0 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:56 a.m.