Triple
T6155275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chrysopolis |
E137304
|
entity |
| Predicate | crossingPointFor |
P50696
|
FINISHED |
| Object | armies |
—
|
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: armies | Statement: [Chrysopolis, crossingPointFor, armies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crossingPointFor Context triple: [Chrysopolis, crossingPointFor, armies]
-
A.
hasCrossingPoint
chosen
Indicates that two or more entities intersect or share at least one common point in space or along their paths.
-
B.
hasNearbyCrossingPoint
Indicates that one location has a crossing point (such as a bridge, crosswalk, or intersection) situated close to it.
-
C.
hadCrossingPoints
Indicates that two entities intersected or overlapped at one or more specific points in space or time.
-
D.
crossingOf
Indicates that one entity serves as the intersection or crossing point of two or more linear features, such as roads, paths, or tracks.
-
E.
crossingStructure
Indicates that one entity serves as a structure enabling passage across or over another entity, such as a bridge, tunnel, or overpass.
- F. None of above.
Provenance (3 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_69c008a45d008190832a9e19f5d63406 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05d01ddb0819085b5f5338b86a25d |
completed | March 22, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69c055f39e0881909ae56444b1b48929 |
completed | March 22, 2026, 8:49 p.m. |
Created at: March 22, 2026, 4:17 p.m.