Triple
T26808458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Butler, Pennsylvania |
E671912
|
entity |
| Predicate | manufacturerLocatedIn |
P35004
|
FINISHED |
| Object | Standard Steel Car Company |
—
|
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: Standard Steel Car Company | Statement: [Butler, Pennsylvania, manufacturerLocatedIn, Standard Steel Car Company]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: manufacturerLocatedIn Context triple: [Butler, Pennsylvania, manufacturerLocatedIn, Standard Steel Car Company]
-
A.
manufacturerLocation
chosen
Indicates the geographic place where a product’s manufacturer is based or operates.
-
B.
assemblyCountry
Indicates the country in which an item, product, or component is assembled.
-
C.
countryOfOrigin
Indicates the country from which an entity originally comes or was first produced, created, or established.
-
D.
engineOriginCountry
Indicates the country where an engine was originally designed, manufactured, or first produced.
-
E.
isProducedIn
Indicates that something is created, manufactured, or generated within a particular place, context, or process.
- 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_69eeb3225a3c8190aaf6746efeded2f3 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f61fd623bc819091df736cf3419b99 |
completed | May 2, 2026, 4:01 p.m. |
| PD | Predicate disambiguation | batch_69f61b3d23f481908dfec27adace900a |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 4:27 a.m.