Triple
T35272248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brooklyn, New York (fictionalized) |
E1018699
|
entity |
| Predicate | fictionalAddressLocatedIn |
P135969
|
FINISHED |
| Object | Huxtable residence |
—
|
NE NERFINISHED |
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: Huxtable residence | Statement: [Brooklyn, New York (fictionalized), fictionalAddressLocatedIn, Huxtable residence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalAddressLocatedIn Context triple: [Brooklyn, New York (fictionalized), fictionalAddressLocatedIn, Huxtable residence]
-
A.
fictionalAddress
Indicates that an address associated with an entity is invented or not corresponding to a real-world location.
-
B.
hasFictionalAddressTown
chosen
Indicates that an entity is associated with a town that serves as its fictional address location.
-
C.
fictionalCountryLocation
Indicates that a fictional country is located within, or geographically associated with, a specified place or region.
-
D.
fictionalBirthPlace
Indicates the fictional location where a character or entity is described as having been born within a narrative or imagined context.
-
E.
stateOfFictionalResidence
Indicates the state or region in which a fictional character’s residence is located.
- 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_69f76de5c4788190896ad598ae7d6bc6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff0214d7348190904688376df99bce |
completed | May 9, 2026, 9:44 a.m. |
| PD | Predicate disambiguation | batch_69feffd62fec8190a855922c8b3c57cf |
completed | May 9, 2026, 9:35 a.m. |
Created at: May 3, 2026, 4:02 p.m.