Triple
T458786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peninsula Commute |
E7289
|
entity |
| Predicate | serviceCharacter |
P5621
|
FINISHED |
| Object | suburban commuter |
—
|
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: suburban commuter | Statement: [Peninsula Commute, serviceCharacter, suburban commuter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceCharacter Context triple: [Peninsula Commute, serviceCharacter, suburban commuter]
-
A.
service
Indicates that one entity performs work, assistance, or functions to meet the needs or requests of another entity.
-
B.
serviceOf
Indicates that one entity performs, provides, or fulfills a function or duty on behalf of another entity.
-
C.
serviceAreaCharacteristic
Indicates a relationship where a service area is associated with a specific attribute or feature that characterizes it.
-
D.
serviceClass
chosen
Indicates the classification or category of service associated with or provided by an entity in the relationship.
-
E.
serviceUniform
Indicates that one entity is wearing or associated with a standardized uniform used for official or professional service.
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efa4a6208190a8243a0e14f84f52 |
completed | Feb. 28, 2026, 1:37 p.m. |
| PD | Predicate disambiguation | batch_69a2ede75b6c81908350103d21f22a03 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.