Triple
T164790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pittsburgh–Chicago route |
E2988
|
entity |
| Predicate | servedIndustrialCenter |
P2193
|
FINISHED |
| Object | Pittsburgh steel 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: Pittsburgh steel industry | Statement: [Pittsburgh–Chicago route, servedIndustrialCenter, Pittsburgh steel industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedIndustrialCenter Context triple: [Pittsburgh–Chicago route, servedIndustrialCenter, Pittsburgh steel industry]
-
A.
isIndustrialCenter
Indicates that a place functions as a major hub of industrial activity, production, or manufacturing within a region.
-
B.
sectorServed
chosen
Indicates the industry or economic sector that an entity primarily serves or targets with its activities, products, or services.
-
C.
servedCity
Indicates that a service, route, or facility operates in, reaches, or is available to a particular city.
-
D.
isMajorCenterOf
Indicates that a place serves as a primary hub or focal point for a particular activity, function, or domain.
-
E.
areaServed
Indicates the geographic region or jurisdiction within which a service, organization, or activity is provided or applicable.
- 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_69a2524ce1e48190ab066bf72859f474 |
completed | Feb. 28, 2026, 2:26 a.m. |
| NER | Named-entity recognition | batch_69a258827da481909b20ea5e9d21676f |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a2566392208190a538ea9aa1fac53e |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:34 a.m.