Triple
T170553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mathematical Bridge |
E3111
|
entity |
| Predicate | spans |
P266
|
FINISHED |
| Object | the River Cam between two parts of Queens' College |
—
|
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: the River Cam between two parts of Queens' College | Statement: [Mathematical Bridge, spans, the River Cam between two parts of Queens' College]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spans Context triple: [Mathematical Bridge, spans, the River Cam between two parts of Queens' College]
-
A.
numberOfSpans
Indicates the total count of distinct spans or segments associated with an entity or within a specified context.
-
B.
lays
Indicates that one entity deposits or places something, typically eggs or objects, onto a surface or in a location.
-
C.
wingspan
Indicates the distance from the tip of one wing to the tip of the other wing when fully extended.
-
D.
length
chosen
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
-
E.
spreadBy
Indicates that something is transmitted, dispersed, or propagated through the agency or action of a specified entity or medium.
- 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_69a2524ce1e48190ab066bf72859f474 |
completed | Feb. 28, 2026, 2:26 a.m. |
| NER | Named-entity recognition | batch_69a25a3f9d188190aacf5791273e2c65 |
completed | Feb. 28, 2026, 3 a.m. |
| PD | Predicate disambiguation | batch_69a25667717c8190bac5108366e2178d |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:34 a.m.