Triple
T28470849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STS-1 |
E720431
|
entity |
| Predicate | hasSectionOverhead |
P194515
|
FINISHED |
| Object | SONET section overhead |
—
|
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: SONET section overhead | Statement: [STS-1, hasSectionOverhead, SONET section overhead]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSectionOverhead Context triple: [STS-1, hasSectionOverhead, SONET section overhead]
-
A.
hasLineOverhead
Indicates that one entity has an overhead line (such as a cable, wire, or similar linear infrastructure) positioned above it or running over it.
-
B.
hasPathOverhead
Indicates that one path crosses above or over another path or area, creating an overhead relationship between them.
-
C.
hasOverheadType
Indicates that one entity is associated with a specific category or type of overhead (such as cost, resource, or operational overhead) that applies to it.
-
D.
hasSectionLength
Indicates that an entity is associated with a specific length value for one of its sections.
-
E.
hasSectionCount
Indicates that an entity is associated with a specific number of sections it contains or comprises.
- 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_69f01a5983f48190b7c1b8857245a4f7 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69fd783fed9c81909e792702636c4f1f |
completed | May 8, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69fd7788e63c81909de22fdafcfe41c0 |
completed | May 8, 2026, 5:41 a.m. |
| PDg | Predicate description generation | batch_69fd783e9e5c819087dec7fefa03700d |
completed | May 8, 2026, 5:44 a.m. |
Created at: April 28, 2026, 2:48 a.m.