Triple
T23516059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess of Genovia |
E574369
|
entity |
| Predicate | holderResidenceBeforeTitle |
P152695
|
FINISHED |
| Object | New York City |
—
|
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: New York City | Statement: [Princess of Genovia, holderResidenceBeforeTitle, New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: holderResidenceBeforeTitle Context triple: [Princess of Genovia, holderResidenceBeforeTitle, New York City]
-
A.
residenceBeforeArrest
Indicates that a person lived at a particular residence prior to the time of their arrest.
-
B.
formerResidenceOf
Indicates that a location was once the place where a person or entity lived or was based, but is no longer their current residence.
-
C.
hasTitleHolderResidence
Indicates that a specified residence is the official home or dwelling place of the current holder of a particular title.
-
D.
residenceBeforeImprisonment
Indicates the place where an individual lived prior to being imprisoned.
-
E.
hasNearbyFormerResidenceOf
Indicates that one entity is located near a place that used to be the residence of another entity.
- 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_69e245bb3dcc8190ba9a2b35972b58d0 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1aa81ab4c8190b85c8f80754020ea |
completed | April 29, 2026, 6:51 a.m. |
| PD | Predicate disambiguation | batch_69f0621165c08190a0b27b1319733959 |
completed | April 28, 2026, 7:30 a.m. |
| PDg | Predicate description generation | batch_69f0bd4a0e408190ad8916faf23562d9 |
completed | April 28, 2026, 1:59 p.m. |
Created at: April 17, 2026, 6:08 p.m.