Triple
T7854511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philadelphia–Harrisburg |
E182138
|
entity |
| Predicate | connectsCityType |
P46659
|
FINISHED |
| Object | largest city of Pennsylvania |
—
|
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: largest city of Pennsylvania | Statement: [Philadelphia–Harrisburg, connectsCityType, largest city of Pennsylvania]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsCityType Context triple: [Philadelphia–Harrisburg, connectsCityType, largest city of Pennsylvania]
-
A.
connectsTypeOfCity
chosen
Indicates a relationship where one entity is linked to another as a specific type or category of city.
-
B.
connectsCity
Indicates a relationship where one entity serves as a link or route that joins or provides direct access between two cities.
-
C.
connectsCityTo
Indicates a relationship in which a route, infrastructure, or link joins one city to another, enabling connection or interaction between them.
-
D.
cityServedType
Indicates the type or category of city that is served by a given entity (such as a facility, service, or infrastructure).
-
E.
connectsMajorCity
Indicates that one entity serves as a link or route providing direct connection to a major city.
- 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_69ca82869ee08190b8f9040dbc2c0467 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb1a72cfdc8190a3186c4c2894f571 |
completed | March 31, 2026, 12:50 a.m. |
| PD | Predicate disambiguation | batch_69cae92180f88190ae3d44c3de7adc93 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:51 p.m.