Triple
T30799214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lidra Caddesi |
E784318
|
entity |
| Predicate | crossesLine |
P50696
|
FINISHED |
| Object | Green Line |
—
|
NE NERFINISHED |
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: Green Line | Statement: [Lidra Caddesi, crossesLine, Green Line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crossesLine Context triple: [Lidra Caddesi, crossesLine, Green Line]
-
A.
hasCrossingPoint
chosen
Indicates that two or more entities intersect or share at least one common point in space or along their paths.
-
B.
crossesNear
Indicates that one entity passes across the path or area of another entity at a location that is close to, but not directly intersecting, the other entity.
-
C.
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.
-
D.
hadCrossingPoints
Indicates that two entities intersected or overlapped at one or more specific points in space or time.
-
E.
crossesSectionOf
Indicates that one entity passes through or over a specific segment or portion of 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_69f224b3a7ec819096939414d103e31e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: April 29, 2026, 8:42 p.m.