Triple
T3198123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rafah Crossing |
E66980
|
entity |
| Predicate | isOnlyDirectCrossingBetween |
P46065
|
FINISHED |
| Object | Gaza Strip and Egypt |
—
|
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: Gaza Strip and Egypt | Statement: [Rafah Crossing, isOnlyDirectCrossingBetween, Gaza Strip and Egypt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOnlyDirectCrossingBetween Context triple: [Rafah Crossing, isOnlyDirectCrossingBetween, Gaza Strip and Egypt]
-
A.
isLocalCrossroads
Indicates that a location serves as a junction where multiple local routes or streets intersect.
-
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.
crossingType
Indicates the specific kind or category of crossing (e.g., how or where one thing passes over, through, or across another).
-
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.
hadCrossingPoints
Indicates that two entities intersected or overlapped at one or more specific points in space or time.
- 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_69ad8588ba18819086a10951c32ecb80 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada7192994819084817307065a25e2 |
completed | March 8, 2026, 4:43 p.m. |
| PD | Predicate disambiguation | batch_69ad9e05e4f48190adbe4366cdba2349 |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada0f9259c8190afbc5ad0fa55436b |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:07 p.m.