Triple
T1726786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Circus, Bath |
E37513
|
entity |
| Predicate | hasNumberOfSegments |
P1905
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [The Circus, Bath, hasNumberOfSegments, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfSegments Context triple: [The Circus, Bath, hasNumberOfSegments, 3]
-
A.
hasMultipleSegments
Indicates that the referenced entity is composed of more than one distinct segment or section.
-
B.
hasLocalSegments
Indicates that an entity is composed of or associated with smaller, distinct segments that exist within a specific local context or region.
-
C.
hasExpressSegments
Indicates that a route, service, or path includes segments that are designated as express, skipping certain intermediate stops or steps.
-
D.
maximumNumberOfSegments
Indicates the greatest allowable or observed count of discrete segments into which something can be or is divided.
-
E.
hasNumberOfDivisions
chosen
Indicates the relationship that specifies how many divisions or subunits an entity possesses.
- 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_69a8861acab88190bb43cde203429399 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aadb7bda1081908f2c41c520c9c55c |
completed | March 6, 2026, 1:49 p.m. |
| PD | Predicate disambiguation | batch_69aa61c0a0288190bce9d60062a84b69 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.