Triple
T38690265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tervingi |
E949240
|
entity |
| Predicate | crossingOfDanube |
P193588
|
FINISHED |
| Object | 376 |
—
|
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: 376 | Statement: [Tervingi, crossingOfDanube, 376]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crossingOfDanube Context triple: [Tervingi, crossingOfDanube, 376]
-
A.
borderingCountryAcrossDanube
Indicates that one country shares a border with another country specifically across the Danube River.
-
B.
crossedByRiver
Indicates that a river passes across or through a specified area, feature, or route.
-
C.
wasMainRiverCrossingUntil
Indicates that a particular river crossing served as the primary or most important crossing point over a river up to a specified time.
-
D.
wasMainRiverCrossingFor
Indicates that one river crossing (such as a bridge, ford, or ferry) served as the primary or most significant crossing point for a particular route, area, or settlement.
-
E.
crossesBorderRiver
Indicates that one entity moves from one side of a border-defining river to the other, traversing the river that serves as a boundary.
- 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_69f76efe16148190befd5dd59c3dfeaa |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd49f6dbac81909744373a357b7982 |
completed | May 8, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69fd48ed68f481908374183c66a6b055 |
completed | May 8, 2026, 2:22 a.m. |
| PDg | Predicate description generation | batch_69fd49f612a4819096fe7d5a3bb439ba |
completed | May 8, 2026, 2:27 a.m. |
Created at: May 3, 2026, 4:33 p.m.