Triple
T35401378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kowalski apartment |
E1023241
|
entity |
| Predicate | frequentVisitorInFiction |
P142221
|
FINISHED |
| Object | Blanche DuBois |
—
|
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: Blanche DuBois | Statement: [Kowalski apartment, frequentVisitorInFiction, Blanche DuBois]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequentVisitorInFiction Context triple: [Kowalski apartment, frequentVisitorInFiction, Blanche DuBois]
-
A.
visitedByFictional
chosen
Indicates that a location or place is (in a story or fictional context) visited by a fictional character or entity.
-
B.
createsInFiction
Indicates that one entity is the creator or originator of another entity within a fictional or narrative context.
-
C.
neighborOfFictional
Indicates that one fictional entity is located next to or in close proximity to another fictional entity within a narrative or imagined setting.
-
D.
eraOfPopularityInFiction
Indicates the historical time period during which a subject is most commonly or prominently depicted in fictional works.
-
E.
associatedPeriodInFiction
Indicates a relationship where a fictional work, character, or event is linked to a specific time period within its fictional universe or narrative setting.
- 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_69f76df43ca4819098711ca4370f1bb9 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79da9f80c8190b0afd8509f28747b |
completed | May 3, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69f79617d40481909ba372f94209c08b |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:03 p.m.