Triple
T20238908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yaviza |
E498226
|
entity |
| Predicate | roadNetworkStatus |
P139360
|
FINISHED |
| Object | terminus of the Inter-American Highway in Panama |
—
|
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: terminus of the Inter-American Highway in Panama | Statement: [Yaviza, roadNetworkStatus, terminus of the Inter-American Highway in Panama]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadNetworkStatus Context triple: [Yaviza, roadNetworkStatus, terminus of the Inter-American Highway in Panama]
-
A.
roadConnectivityStatus
Indicates the current state of whether and how well two locations are connected by a road network.
-
B.
roadSystem
Indicates a relationship where multiple roads are organized and connected as part of a larger, integrated transportation network or infrastructure.
-
C.
roadNetworkContext
Indicates the contextual relationship between elements within a road network, such as how roads, intersections, and related infrastructure are organized or interact.
-
D.
roadAffected
Indicates that a road is impacted or disrupted by a condition, event, or action, such as construction, accidents, or adverse weather.
-
E.
roadTraffic
Indicates the presence, flow, or conditions of vehicles and movement along roads or streets.
- 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_69da6274c58c81909c646eabed6f4f30 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6716c8de88190916bfa1d6b7f79cb |
completed | April 20, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69e55b1b23f88190bdcbe2f81dd226dd |
completed | April 19, 2026, 10:45 p.m. |
| PDg | Predicate description generation | batch_69e56702ad04819099c1c08f28d16809 |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 11, 2026, 11:40 p.m.