Triple
T2659436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ponce de Leon, Florida |
E54690
|
entity |
| Predicate | primaryTransportationMode |
P1379
|
FINISHED |
| Object | automobile |
—
|
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: automobile | Statement: [Ponce de Leon, Florida, primaryTransportationMode, automobile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryTransportationMode Context triple: [Ponce de Leon, Florida, primaryTransportationMode, automobile]
-
A.
primaryTransportModel
Indicates that one transport model is designated as the main or default model used for a given context or entity.
-
B.
passesUsedForTransportation
Indicates that the passes are utilized as a means or instrument for transporting people or goods.
-
C.
transportType
chosen
Indicates the mode or means of transportation used in carrying something or someone from one place to another.
-
D.
publicTransitMode
Indicates the type of public transportation (e.g., bus, train, subway) used or associated with a given trip or segment.
-
E.
transportation
Indicates the movement of someone or something from one place to another, typically using a vehicle or transit system.
- 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_69ab49e028948190b97e01d73548b1d9 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd94f3b1881909bd36cfe61c254a5 |
completed | March 7, 2026, 7:52 a.m. |
| PD | Predicate disambiguation | batch_69abd81768748190bd965f367cf6ef37 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.