Triple
T1505079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Mateo–Hayward Bridge |
E33880
|
entity |
| Predicate | hasHighRiseSpan |
P29449
|
FINISHED |
| Object | shipping channel span |
—
|
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: shipping channel span | Statement: [San Mateo–Hayward Bridge, hasHighRiseSpan, shipping channel span]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighRiseSpan Context triple: [San Mateo–Hayward Bridge, hasHighRiseSpan, shipping channel span]
-
A.
hasUpperFloor
Indicates that one entity possesses or includes an upper floor relative to another level or reference point.
-
B.
hasTowerHeight
Indicates that an entity (such as a tower or structure) has a specific height value associated with it.
-
C.
hasHigh
Indicates that an entity possesses a high level, degree, or intensity of a specified attribute or property.
-
D.
hasHeight
Indicates that one entity possesses a specific vertical measurement or stature.
-
E.
hasBuildingHeightType
Indicates the classification or type used to characterize the height of a building in the relationship.
- 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_69a885f352a4819099b24ff15489dede |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90584b8b881908e112c7e59163812 |
completed | March 5, 2026, 4:24 a.m. |
| PD | Predicate disambiguation | batch_69a88727ce48819089b482cdc25453d1 |
completed | March 4, 2026, 7:25 p.m. |
| PDg | Predicate description generation | batch_69a90582f2548190bc0a6bdcd6d9d015 |
completed | March 5, 2026, 4:24 a.m. |
Created at: March 4, 2026, 7:24 p.m.