Triple
T10102777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antero de Quental metro station |
E216241
|
entity |
| Predicate | hasCustomerServiceDesk |
P31157
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Antero de Quental metro station, hasCustomerServiceDesk, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCustomerServiceDesk Context triple: [Antero de Quental metro station, hasCustomerServiceDesk, yes]
-
A.
hasCustomerServices
Indicates that an entity provides or is associated with one or more customer service functions or offerings.
-
B.
hasCustomerAssistanceArea
chosen
Indicates that an entity includes or provides a designated area or facility for assisting customers.
-
C.
hasCustomerServiceChannel
Indicates that an entity provides or is associated with a specific channel or medium through which customer service interactions can occur.
-
D.
hasFrontDesk
Indicates that one entity provides or is equipped with a front desk service or reception area for another entity.
-
E.
hasServiceCenter
Indicates that an entity maintains or is associated with a service center that provides support, repair, or maintenance services.
- 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_69ca83d039f08190b9d10363221c69fb |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd09af07c819099774af46ebf62d7 |
completed | April 2, 2026, 2:12 a.m. |
| PD | Predicate disambiguation | batch_69cd4b9b853c8190a2af993ce9b21309 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:02 p.m.