Triple
T9114530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanctum Sanctorum |
E218690
|
entity |
| Predicate | streetAddressFictional |
P14481
|
FINISHED |
| Object | 177A Bleecker Street |
—
|
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: 177A Bleecker Street | Statement: [Sanctum Sanctorum, streetAddressFictional, 177A Bleecker Street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: streetAddressFictional Context triple: [Sanctum Sanctorum, streetAddressFictional, 177A Bleecker Street]
-
A.
fictionalAddress
chosen
Indicates that an address associated with an entity is invented or not corresponding to a real-world location.
-
B.
streetAddress
Indicates the specific location of an entity in terms of its numbered building and street name within a postal address.
-
C.
streetLocation
Indicates that one entity is located on, along, or at a specific street associated with the other entity.
-
D.
address
Indicates that one entity directs spoken or written communication specifically to another entity.
-
E.
hasStreet
Indicates that an entity is located on, associated with, or identified by a particular street.
- 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_69ca83dc94ac8190b9ef42684d36ff39 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca84c209c8190b082a9b8499bedf7 |
completed | April 1, 2026, 5:08 a.m. |
| PD | Predicate disambiguation | batch_69cc65fe5be081909d4470d6317b14a6 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:16 p.m.