Triple
T12671356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arconia apartment building |
E302688
|
entity |
| Predicate | buildingTypeInFiction |
P71478
|
FINISHED |
| Object | luxury cooperative |
—
|
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: luxury cooperative | Statement: [Arconia apartment building, buildingTypeInFiction, luxury cooperative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buildingTypeInFiction Context triple: [Arconia apartment building, buildingTypeInFiction, luxury cooperative]
-
A.
fictionalBuilding
Indicates that a building is imaginary or exists only within a fictional or invented context.
-
B.
architectInFiction
Indicates that an entity appears as an architect within a fictional work or narrative context.
-
C.
hasFictionalEstablishmentType
chosen
Indicates that an establishment is associated with a particular type or category of fictional setting or institution.
-
D.
buildingType
Indicates the specific category or function that characterizes what kind of building something is.
-
E.
fictionalEntityType
Indicates that the subject is classified as a particular type or category of fictional entity within a narrative or imaginary 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960bb64ec8190bd0400cf0cc8b0a7 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:20 p.m.