Triple
T11945858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Longleaf Trace |
E284296
|
entity |
| Predicate | usesFormerRouteOf |
P102403
|
FINISHED |
| Object | railroad line |
—
|
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: railroad line | Statement: [Longleaf Trace, usesFormerRouteOf, railroad line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesFormerRouteOf Context triple: [Longleaf Trace, usesFormerRouteOf, railroad line]
-
A.
formerRouteNumber
Indicates that an entity previously had a specific route number before being renumbered, discontinued, or otherwise changed.
-
B.
followsRouteOf
Indicates that one entity travels along the same path or route that another entity takes or has taken.
-
C.
previousRoute
Indicates that one route directly precedes another in an ordered sequence of routes.
-
D.
hadRoute
Indicates that an entity (such as a service, vehicle, or system) followed, operated on, or was associated with a specific route.
-
E.
usedRoutes
Indicates that an entity has utilized or traveled along specific routes.
- 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903456ec0819082b8b10755a6b732 |
completed | April 10, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3e48e08190b2fee43af4f57323 |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8dd0ba0f88190b7d5e358c27ca184 |
completed | April 10, 2026, 11:20 a.m. |
Created at: April 8, 2026, 9:45 p.m.