Triple
T30794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Camino Real |
E613
|
entity |
| Predicate | hasSpeedLimit |
P2129
|
FINISHED |
| Object | typically between 30 and 45 miles per hour |
—
|
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: typically between 30 and 45 miles per hour | Statement: [El Camino Real, hasSpeedLimit, typically between 30 and 45 miles per hour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpeedLimit Context triple: [El Camino Real, hasSpeedLimit, typically between 30 and 45 miles per hour]
-
A.
hasLimitation
Indicates that an entity is subject to a constraint, restriction, or boundary that limits its scope, capability, or applicability.
-
B.
fareControl
Indicates that an entity is responsible for monitoring, enforcing, or managing payment of fares for access to a service or facility.
-
C.
hasMajorHighway
Indicates that a location or area is served by or directly connected to a major highway route.
-
D.
hasGroundTransportation
Indicates that an entity provides, includes, or is connected to transportation services or options that operate on land (e.g., cars, buses, trains).
-
E.
hasParking
Indicates that a place or facility provides designated parking space(s) available for use.
- 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.