Triple
T19454239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Family Video (Hawkins) |
E486694
|
entity |
| Predicate | hasFictionalAddressDetail |
P14481
|
FINISHED |
| Object | strip mall in Hawkins |
—
|
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: strip mall in Hawkins | Statement: [Family Video (Hawkins), hasFictionalAddressDetail, strip mall in Hawkins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalAddressDetail Context triple: [Family Video (Hawkins), hasFictionalAddressDetail, strip mall in Hawkins]
-
A.
hasFictionalAddressStatus
Indicates that an entity’s address is designated as fictional rather than a real-world, verifiable location.
-
B.
hasFictionalHouseNumberRange
Indicates that an entity is associated with a range of house numbers that are fictional or not used in real-world addressing.
-
C.
fictionalAddress
chosen
Indicates that an address associated with an entity is invented or not corresponding to a real-world location.
-
D.
hasAddress
Indicates that an entity is associated with a specific address or location.
-
E.
hasFictionalProprietor
Indicates that something is owned, managed, or run by a fictional character or entity within a narrative context.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633c117ac8190a38c01c3191beaea |
completed | April 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7499a4819082bec0be8afba35c |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:38 p.m.