Triple
T34925219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marie Barone |
E1007263
|
entity |
| Predicate | hasResidenceInSeries |
P159083
|
FINISHED |
| Object |
Long Island
Long Island is a densely populated island in southeastern New York known for its suburban communities, beaches, and proximity to New York City.
|
E17071
|
NE FINISHED |
How this triple was built (3 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: Long Island | Statement: [Marie Barone, hasResidenceInSeries, Long Island]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Long Island Triple: [Marie Barone, hasResidenceInSeries, Long Island]
Generated description
Long Island is a densely populated island in southeastern New York known for its suburban communities, beaches, and proximity to New York City.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasResidenceInSeries Context triple: [Marie Barone, hasResidenceInSeries, Long Island]
-
A.
residesDuringSeries
chosen
Indicates that one entity lives or is based in a particular place for the duration of a specified series or sequence of events.
-
B.
hasResidenceIn
Indicates that an entity lives or maintains a primary dwelling in a specified location.
-
C.
hasResidenceOn
Indicates that one entity’s place of residence is located on or along another entity, such as a street, road, or other linear feature.
-
D.
inResidenceAt
Indicates that an entity lives or resides at a particular location or residence.
-
E.
hasResidency
Indicates that an entity holds an official, legally recognized residential status in a particular place or jurisdiction.
- F. None of above.
Provenance (6 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_69f76dc3d83881909d5c3c14455cfa2c |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a37a8b318f481909e01ec8d09465cc0 |
completed | June 21, 2026, 9:02 a.m. |
| NEDg | Description generation | batch_6a37a976d678819085e155f8799a1673 |
completed | June 21, 2026, 9:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a37aa2b1fd08190a7e216e6c6402e48 |
completed | June 21, 2026, 9:08 a.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4 p.m.