Triple
T2095505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interstate 110 (Florida) |
E32770
|
entity |
| Predicate | hasBridgeOrViaductSections |
P17088
|
FINISHED |
| Object | elevated freeway segments in Pensacola |
—
|
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: elevated freeway segments in Pensacola | Statement: [Interstate 110 (Florida), hasBridgeOrViaductSections, elevated freeway segments in Pensacola]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBridgeOrViaductSections Context triple: [Interstate 110 (Florida), hasBridgeOrViaductSections, elevated freeway segments in Pensacola]
-
A.
hasBridgeSection
Indicates that one entity includes or is associated with a specific bridge section as a distinct part or component.
-
B.
hasViaduct
chosen
Indicates that one entity possesses, includes, or is connected by a viaduct in relation to another entity.
-
C.
hasNumberOfBridges
Indicates the quantitative relationship specifying how many bridges are associated with a given entity.
-
D.
hasBridgeTunnel
Indicates that there exists a bridge or tunnel connection between two locations or structures.
-
E.
hasPassengerBridge
Indicates that one entity is connected to another by a bridge or walkway specifically designed for passengers to move between them.
- 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_69a885eba0708190999696a45cbec816 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abba99ddc48190bb2097b56efb7aca |
completed | March 7, 2026, 5:41 a.m. |
| PD | Predicate disambiguation | batch_69abb7b6274081909df36cd7a7c6a675 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.