Triple
T4449449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trinity Bridge, Manchester |
E96370
|
entity |
| Predicate | hasPylonType |
P32602
|
FINISHED |
| Object | inclined steel pylon |
—
|
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: inclined steel pylon | Statement: [Trinity Bridge, Manchester, hasPylonType, inclined steel pylon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPylonType Context triple: [Trinity Bridge, Manchester, hasPylonType, inclined steel pylon]
-
A.
hasPylon
chosen
Indicates that one entity possesses, includes, or is equipped with a pylon as part of its structure or configuration.
-
B.
hasPylonCount
Indicates the relationship specifying how many pylons are associated with or present in a given entity.
-
C.
hasPylonHeight
Indicates that an entity is associated with a specific height value of a pylon.
-
D.
pylonType
Indicates the specific structural or functional category that a pylon belongs to within a given context.
-
E.
hasPilotType
Indicates that an entity has or is associated with a specific type or category of pilot.
- 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_69b345415ba481908df738e7174448ba |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355d5975c8190bfe8a2d5d2dbf075 |
completed | March 13, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69b34f62c180819097ced38da2052207 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:32 p.m.