Triple
T28039374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Avenue South Bridge |
E708494
|
entity |
| Predicate | hasBasculeLeaves |
P38021
|
FINISHED |
| Object | two |
—
|
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: two | Statement: [First Avenue South Bridge, hasBasculeLeaves, two]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBasculeLeaves Context triple: [First Avenue South Bridge, hasBasculeLeaves, two]
-
A.
hasBasculeMechanism
Indicates that one entity is equipped with or incorporates a bascule (pivoting or counterweighted) mechanism provided by the other entity.
-
B.
hasLeaves
chosen
Indicates that an entity possesses leaves as part of its structure or form.
-
C.
hasLanes
Indicates that an entity, such as a road or pathway, is divided into one or more distinct lanes for traffic or movement.
-
D.
hasBridges
Indicates that one entity possesses, contains, or is characterized by one or more bridges connecting locations or components.
-
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_69ef9b6cf538819094a633ffa67afec1 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f6c1265c208190aacd2b551f8f0f82 |
completed | May 3, 2026, 3:29 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2415fc81908c23c311aebce66f |
completed | May 3, 2026, 3:12 a.m. |
Created at: April 27, 2026, 8:23 p.m.