Triple
T17793581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 99th Precinct |
E444229
|
entity |
| Predicate | hasFictionalAddressStatus |
P128940
|
FINISHED |
| Object | unspecified in detail on-screen |
—
|
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: unspecified in detail on-screen | Statement: [99th Precinct, hasFictionalAddressStatus, unspecified in detail on-screen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalAddressStatus Context triple: [99th Precinct, hasFictionalAddressStatus, unspecified in detail on-screen]
-
A.
hasAddressState
Indicates that an entity’s address is located within a particular state or state-level administrative region.
-
B.
hasAddress
Indicates that an entity is associated with a specific address or location.
-
C.
hasFictionalHouseNumberRange
Indicates that an entity is associated with a range of house numbers that are fictional or not used in real-world addressing.
-
D.
hasFictionalProprietor
Indicates that something is owned, managed, or run by a fictional character or entity within a narrative context.
-
E.
hasFictionalPostcode
Indicates that an entity is associated with a postcode that is invented or not used in the real-world postal system.
- 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_69d8b9efe370819095cd219b143ae727 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e487993a6c8190805e06d93dfc0dce |
completed | April 19, 2026, 7:43 a.m. |
| PD | Predicate disambiguation | batch_69e3d8d8e538819084f1584426b41d5e |
completed | April 18, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69e3db7704588190a34a422421152173 |
completed | April 18, 2026, 7:28 p.m. |
Created at: April 10, 2026, 10:13 a.m.