Triple
T18100405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allenby Bridge – West Bank and Jordan |
E433197
|
entity |
| Predicate | hasBridgeStructure |
P121738
|
FINISHED |
| Object | road bridge |
—
|
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: road bridge | Statement: [Allenby Bridge – West Bank and Jordan, hasBridgeStructure, road bridge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBridgeStructure Context triple: [Allenby Bridge – West Bank and Jordan, hasBridgeStructure, road bridge]
-
A.
hasBridgeOrStructure
Indicates that there exists a bridge or similar structural connection between the related entities.
-
B.
hasBridgeTo
Indicates that one entity is connected to another by a bridge or bridging structure that allows passage or linkage between them.
-
C.
hasBridgeSection
Indicates that one entity includes or is associated with a specific bridge section as a distinct part or component.
-
D.
bridgeStructure
chosen
Indicates a structural relationship where one entity functions as a bridge that spans or connects two separate points or areas.
-
E.
hasNumberOfBridges
Indicates the quantitative relationship specifying how many bridges are associated with a given entity.
- 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddb5e6208190b3c3cce3b95d66ad |
completed | April 19, 2026, 1:50 p.m. |
| PD | Predicate disambiguation | batch_69e4330e1f2881908b2506d47c48736b |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:27 a.m.