Triple
T37376062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbary Lane boarding house |
E927983
|
entity |
| Predicate | fictionalStreetAddress |
P198219
|
FINISHED |
| Object | 28 Barbary Lane |
—
|
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: 28 Barbary Lane | Statement: [Barbary Lane boarding house, fictionalStreetAddress, 28 Barbary Lane]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalStreetAddress Context triple: [Barbary Lane boarding house, fictionalStreetAddress, 28 Barbary Lane]
-
A.
fictionalAddress
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.
fictionalStreetContext
Indicates that the relationship or action occurs within a fictional street setting or is contextualized by events, conditions, or features specific to an imagined street.
-
D.
hasFictionalAddressTown
Indicates that an entity is associated with a town that serves as its fictional address location.
-
E.
hasFictionalAddressElement
chosen
Indicates that an entity includes an address component that is invented or not intended to correspond to a real-world location.
- 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_69f76eb820248190a5c395ca50ad002a |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff6074bcd4819090b72cd6209ff206 |
completed | May 9, 2026, 4:27 p.m. |
| PD | Predicate disambiguation | batch_69ff600aba888190812a6e7eca0283b8 |
completed | May 9, 2026, 4:25 p.m. |
Created at: May 3, 2026, 4:16 p.m.