Triple
T35919171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | W Broadway Local |
E1038832
|
entity |
| Predicate | hasServiceSymbol |
P57607
|
FINISHED |
| Object | W |
—
|
NE NERFINISHED |
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: W | Statement: [W Broadway Local, hasServiceSymbol, W]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasServiceSymbol Context triple: [W Broadway Local, hasServiceSymbol, W]
-
A.
hasServiceSymbolText
chosen
Indicates that a service symbol is associated with a specific textual representation.
-
B.
hasServiceSymbolShape
Indicates that an entity’s service symbol is represented using a particular geometric or visual shape.
-
C.
hasServiceClass
Indicates that an entity is associated with, or categorized under, a particular class or type of service.
-
D.
hasServiceFunction
Indicates that an entity performs, provides, or is responsible for a particular service-related function or role.
-
E.
hasServiceModule
Indicates that an entity is equipped with, or associated with, a specific service module that provides supporting or auxiliary functions.
- 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_69f76e2320748190b7f5c4750d0cd0d3 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a00315632a8819092290f455babd7ee |
completed | May 10, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_6a002f54a0dc81909b0e54c5e110e67c |
completed | May 10, 2026, 7:10 a.m. |
Created at: May 3, 2026, 4:07 p.m.