Triple
T7333389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peterborough Lift Lock |
E169061
|
entity |
| Predicate | hasTwinCaissons |
P77100
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Peterborough Lift Lock, hasTwinCaissons, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTwinCaissons Context triple: [Peterborough Lift Lock, hasTwinCaissons, yes]
-
A.
hasArchitecturalTwin
Indicates that two entities share nearly identical architectural design, form, or structure, effectively making them architectural counterparts or duplicates.
-
B.
hasTwinFeature
Indicates that two entities share an identical or nearly identical feature, characteristic, or component, as if they are twins in that respect.
-
C.
twinType
Indicates that one entity is classified as a specific type or category of twin in relation to another entity.
-
D.
hasTwin
Indicates that one entity is a twin of another, sharing the same birth event or time with a sibling.
-
E.
hasTwinCityStructure
Indicates that one city has an officially recognized twin-city (sister-city) relationship structure with another city.
- 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_69c68a568a6481908f11e20db7bc8446 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f347f25081908e6086d4073295f5 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f028fd748190b2ea5c3081958a42 |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f3463d0481908aed9ed43a8ac6a8 |
completed | March 27, 2026, 9:14 p.m. |
Created at: March 27, 2026, 3:04 p.m.