Triple
T33282184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siemens SD-400 |
E852075
|
entity |
| Predicate | usedInMetroArea |
P5322
|
FINISHED |
| Object | St. Louis metropolitan area |
—
|
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: St. Louis metropolitan area | Statement: [Siemens SD-400, usedInMetroArea, St. Louis metropolitan area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInMetroArea Context triple: [Siemens SD-400, usedInMetroArea, St. Louis metropolitan area]
-
A.
isWithinMetroArea
Indicates that one location lies inside the geographic boundaries of a specified metropolitan area.
-
B.
operatesInMetropolitanArea
chosen
Indicates that an entity conducts its activities or provides its services within a specified metropolitan area.
-
C.
usedInCity
Indicates that something is utilized, applied, or operates within the context or boundaries of a particular city.
-
D.
locatedNearMetropolitanArea
Indicates that one entity is situated in close geographic proximity to a metropolitan (urban) area.
-
E.
appliesToUrbanArea
Indicates that the relationship, rule, or condition is specifically relevant or applicable to an urban area.
- 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_69f349653da08190819876015a298fdb |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fe5c1a502081909d4024e514309c8e |
completed | May 8, 2026, 9:56 p.m. |
| PD | Predicate disambiguation | batch_69fe5a9df21c819087153f5d0bcaa987 |
completed | May 8, 2026, 9:50 p.m. |
Created at: May 1, 2026, 1:32 a.m.