Triple
T2907952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phrygia |
E63610
|
entity |
| Predicate | crossroadsOf |
P13518
|
FINISHED |
| Object | Greek world |
—
|
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: Greek world | Statement: [Phrygia, crossroadsOf, Greek world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crossroadsOf Context triple: [Phrygia, crossroadsOf, Greek world]
-
A.
wasCrossroadsOf
chosen
Indicates that a place served as a central junction or meeting point where multiple routes, paths, or influences converged.
-
B.
crossesBetween
Indicates that one entity passes from one side of a second entity to the other, traversing the space between two reference points or boundaries associated with that second entity.
-
C.
crossedBy
Indicates that one entity (typically a path, line, or boundary) is intersected or traversed by another entity.
-
D.
crossesTo
Indicates that one entity moves or extends from one side or area to another, passing over or through some boundary or intervening space.
-
E.
oftenCrossedOn
Indicates that one entity is frequently traversed or passed over by another entity.
- 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_69ab4c44ab448190b9411324e8a1fc1d |
completed | March 6, 2026, 9:51 p.m. |
| NER | Named-entity recognition | batch_69abe0d1dcf881909b3ae58d7cdfd9cd |
completed | March 7, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69abdd19bac881908f047d616aca8438 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:11 p.m.