Triple
T34903730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chaumont Viaduct |
E1006662
|
entity |
| Predicate | hasMultipleTiersOfArches |
P196337
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Chaumont Viaduct, hasMultipleTiersOfArches, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMultipleTiersOfArches Context triple: [Chaumont Viaduct, hasMultipleTiersOfArches, true]
-
A.
hasNumberOfArches
Indicates the relationship specifying how many arches are present in or associated with a given entity.
-
B.
hasMiddleTierArches
Indicates that an entity possesses arches specifically located in the middle tier or level of its structure.
-
C.
hasArchedEntrances
Indicates that an entity features one or more entrances constructed with an arched shape.
-
D.
widthOfArches
Indicates the measurement of how wide the arches are in a given structure or context.
-
E.
hasNumberOfArchitecturalOrders
Indicates the specific count of architectural orders associated with or present in a given structure or architectural element.
- 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_69f76dc1b4a081909b4c6e4d8ec0aa2d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe21b0cba48190b56c39e9f1c0eafa |
completed | May 8, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69fe204576848190aecf204e2adba5dc |
completed | May 8, 2026, 5:41 p.m. |
| PDg | Predicate description generation | batch_69fe21afdc4c8190913ac4b55a9a5f52 |
completed | May 8, 2026, 5:47 p.m. |
Created at: May 3, 2026, 4 p.m.