Triple
T4884466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lebanon–Israel border |
E109405
|
entity |
| Predicate | hasDemarcationType |
P3951
|
FINISHED |
| Object | land border |
—
|
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: land border | Statement: [Lebanon–Israel border, hasDemarcationType, land border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDemarcationType Context triple: [Lebanon–Israel border, hasDemarcationType, land border]
-
A.
demarcationType
chosen
Indicates the specific way in which a boundary or separation between entities is defined, marked, or categorized.
-
B.
hasBoundaryType
Indicates that one entity has a boundary characterized by a specific type or classification in relation to another entity or context.
-
C.
hasSegmentType
Indicates that an entity is associated with, or classified by, a particular type or category of segment within a larger structure or sequence.
-
D.
hasBoundaryFeature
Indicates that a boundary (such as an edge, border, or limit) of one entity is characterized, marked, or defined by a specific feature or element.
-
E.
hasTypeOfSubdivision
Indicates that one administrative or territorial unit is classified as a specific kind or category of subdivision.
- 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_69bd440f71348190b99938e59fb7f9a1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6de253ac8190b1112da6953fa4f2 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2be5e881909f6ec9c3bcde49f3 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:27 p.m.