Triple
T32512438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walnut Street, Springfield |
E830971
|
entity |
| Predicate | hasFictionalAddressElement |
P198219
|
FINISHED |
| Object | 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: street | Statement: [Walnut Street, Springfield, hasFictionalAddressElement, street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalAddressElement Context triple: [Walnut Street, Springfield, hasFictionalAddressElement, street]
-
A.
hasFictionalAddressStatus
Indicates that an entity’s address is designated as fictional rather than a real-world, verifiable location.
-
B.
hasFictionalAddressTown
Indicates that an entity is associated with a town that serves as its fictional address location.
-
C.
hasFictionalAddressee
Indicates that an entity (such as a text or communication) is directed toward or addressed to an addressee that is fictional rather than a real person or audience.
-
D.
hasFictionalHouseNumberRange
Indicates that an entity is associated with a range of house numbers that are fictional or not used in real-world addressing.
-
E.
hasAddress
Indicates that an entity is associated with a specific address or location.
- 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_69f3492318348190ba37fb6b5f1d67f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fed357b2b4819084c709056a54461f |
completed | May 9, 2026, 6:25 a.m. |
| PD | Predicate disambiguation | batch_69fed103d9cc81909b11619745110c61 |
completed | May 9, 2026, 6:15 a.m. |
| PDg | Predicate description generation | batch_69fed3569ca881909f4291baeb665d9d |
completed | May 9, 2026, 6:25 a.m. |
Created at: May 1, 2026, 1 a.m.