Triple
T32956493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Office Bridge |
E843114
|
entity |
| Predicate | hasWalkwayWidth |
P182863
|
FINISHED |
| Object | about 3 feet |
—
|
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: about 3 feet | Statement: [Office Bridge, hasWalkwayWidth, about 3 feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWalkwayWidth Context triple: [Office Bridge, hasWalkwayWidth, about 3 feet]
-
A.
hasWalkwayShape
Indicates that a walkway possesses a particular geometric or structural shape or configuration.
-
B.
hasWalkwayPosition
Indicates the spatial or relative position of an entity along or within a walkway.
-
C.
walkwayType
Indicates the specific kind or classification of a walkway associated with an entity (e.g., sidewalk, footpath, boardwalk).
-
D.
hasWalkwaysAndQuads
Indicates that an entity includes or is characterized by walkways and quadrangle areas as part of its layout or structure.
-
E.
hasEmergencyWalkway
Indicates that there is a designated emergency walkway available or present between the related entities.
- 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_69f3494af2808190ad98cec2f1bc0fe6 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f794f24e588190965e39b77534d53f |
completed | May 3, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69f791033d288190b118029fe412b9c9 |
completed | May 3, 2026, 6:16 p.m. |
| PDg | Predicate description generation | batch_69f791cad5e08190a8a04ca283dbecaa |
completed | May 3, 2026, 6:19 p.m. |
Created at: May 1, 2026, 1:21 a.m.