Triple
T3394152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sansome Street |
E71487
|
entity |
| Predicate | hasStreetNumberingSystem |
P49387
|
FINISHED |
| Object | San Francisco street grid |
—
|
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: San Francisco street grid | Statement: [Sansome Street, hasStreetNumberingSystem, San Francisco street grid]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStreetNumberingSystem Context triple: [Sansome Street, hasStreetNumberingSystem, San Francisco street grid]
-
A.
hasJunctionNumbering
Indicates that a road or route is assigned a specific numbering system for its junctions or intersections.
-
B.
hasJunctionNumberingScheme
Indicates the specific system or method used to assign numbers to junctions within a network (such as roads or railways).
-
C.
hasStreetNamingPattern
Indicates that there is a characteristic or systematic way in which streets are named in relation to a given entity.
-
D.
hasRailwayStationNumberingSystem
Indicates that a railway station is associated with a specific system for assigning it an identifying number or code.
-
E.
hasNumberSystem
Indicates that an entity possesses or uses a particular system for representing and organizing numbers.
- 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_69ad85a9c4a88190a854019341cb3b60 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb853746c8190bfa1447e6ebbefb3 |
completed | March 8, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69adadf705608190975423779430cc58 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb2e426b88190b82d9830149b142e |
completed | March 8, 2026, 5:33 p.m. |
Created at: March 8, 2026, 3:14 p.m.