Triple
T14980349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lahij Governorate |
E373556
|
entity |
| Predicate | borderTypeWithAden |
P35564
|
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: [Lahij Governorate, borderTypeWithAden, land border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderTypeWithAden Context triple: [Lahij Governorate, borderTypeWithAden, land border]
-
A.
borderArea
Indicates that an area lies along or near the boundary between two regions, countries, or territories.
-
B.
borderColor
Indicates the color that forms the boundary or outline of an entity.
-
C.
hadBorderType
Indicates that a boundary between two entities existed and specifies the nature or classification of that border (e.g., land, maritime, disputed).
-
D.
sharesBorderType
chosen
Indicates that two entities are connected by a common boundary characterized by the same specified type of border (e.g., land, river, maritime).
-
E.
borderSectionOf
Indicates that one entity represents a specific segment or portion of the overall border 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6fcebf481909f72cab577560d82 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a6169b48190a679609febd2d0e3 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:52 a.m.