Triple
T26271315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Farragut Crossing (virtual tunnel) |
E660429
|
entity |
| Predicate | physicalTunnel |
P160187
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [Farragut Crossing (virtual tunnel), physicalTunnel, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: physicalTunnel Context triple: [Farragut Crossing (virtual tunnel), physicalTunnel, no]
-
A.
tunnels
Indicates that one entity passes through, under, or within another entity via a tunnel-like passage or structure.
-
B.
partOfTunnel
Indicates that one entity forms a physical segment or component within the structure or extent of a tunnel.
-
C.
tunnelType
Indicates the specific kind or classification of a tunnel associated with an entity.
-
D.
tunnelLocation
Indicates that one entity is the location or site where a tunnel is situated or passes through in relation to another entity.
-
E.
tunnelUse
Indicates that one entity makes use of or passes through a tunnel associated with another entity.
- 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_69ee812960d081909cff6085cc9fa3a6 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f60e31255481909a876eeb16338bf1 |
completed | May 2, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69f5f7ff548c8190a23e98c5e66e0bc7 |
completed | May 2, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69f5ffc6268c8190b63f6360ebadab73 |
completed | May 2, 2026, 1:44 p.m. |
Created at: April 26, 2026, 9:50 p.m.