Triple
T30760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Camino Real |
E613
|
entity |
| Predicate | followsRouteOf |
P2127
|
FINISHED |
| Object | historic route connecting Spanish missions in California |
—
|
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: historic route connecting Spanish missions in California | Statement: [El Camino Real, followsRouteOf, historic route connecting Spanish missions in California]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsRouteOf Context triple: [El Camino Real, followsRouteOf, historic route connecting Spanish missions in California]
-
A.
follows
Indicates that one entity comes after, moves behind, or acts in accordance with another entity in time, space, or sequence.
-
B.
followsCoast
Indicates that one entity’s path or boundary runs alongside and generally conforms to the shape of a coastline.
-
C.
hasEasiestRoute
Indicates that one entity provides or represents the simplest or least difficult route or path to reach another entity or destination.
-
D.
isMajorRouteFor
Indicates that something serves as a primary or heavily used pathway or channel for the movement or flow of something else.
-
E.
routeNumber
Indicates the specific identifying number assigned to a route within a transportation or delivery network.
- F. None of above. chosen
Provenance (4 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a2490d80a0819083bf604c1229e903 |
completed | Feb. 28, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69a2486eb01881909241540dda28e1ff |
completed | Feb. 28, 2026, 1:44 a.m. |
| PDg | Predicate description generation | batch_69a2490c9c348190bf8536a08415b94a |
completed | Feb. 28, 2026, 1:46 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.