Triple
T5479465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OSPF |
E123434
|
entity |
| Predicate | hasSpecialArea |
P6822
|
FINISHED |
| Object | backbone area |
—
|
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: backbone area | Statement: [OSPF, hasSpecialArea, backbone area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpecialArea Context triple: [OSPF, hasSpecialArea, backbone area]
-
A.
hasSpecial
Indicates that an entity possesses or is associated with a distinctive or exceptional attribute, status, or feature compared to others.
-
B.
hasAreaType
chosen
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
C.
hasSpecialCategory
Indicates that an entity is associated with a designated special or exceptional category distinct from its standard classifications.
-
D.
hasSpecialUnit
Indicates that an entity possesses or is associated with a distinct, designated unit that has a special role, function, or status.
-
E.
hasProtectedArea
Indicates that an entity possesses, includes, or is associated with a designated protected area for conservation or restricted use.
- 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_69bd4648883481909e9775d43300c5fa |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd9247a16c8190ac5a02534da48853 |
completed | March 20, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69bd91a58c448190904964a439045e05 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:09 p.m.