Triple
T5006631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jackson Square, San Francisco |
E112510
|
entity |
| Predicate | streetCharacter |
P43747
|
FINISHED |
| Object | narrow streets |
—
|
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: narrow streets | Statement: [Jackson Square, San Francisco, streetCharacter, narrow streets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: streetCharacter Context triple: [Jackson Square, San Francisco, streetCharacter, narrow streets]
-
A.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
B.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
-
C.
streetFunction
chosen
Indicates the functional role or primary use of a street within a transportation or urban context (e.g., residential, arterial, commercial access).
-
D.
regionCharacter
Indicates a characteristic, feature, or quality that typifies or defines a particular region.
-
E.
cycleCharacter
Indicates that one character in a sequence is followed by another in a repeating (cyclic) order.
- 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_69bd4433d0b08190877e83959ef40d81 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd730a7590819088ab8d49c5c88c2f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd714cbc448190aa53a8a83d768b64 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:35 p.m.