Triple
T7233359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Lázaro metro station |
E154956
|
entity |
| Predicate | openedWithSection |
P75924
|
FINISHED |
| Object | Line 1 section Zaragoza–Chapultepec |
—
|
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: Line 1 section Zaragoza–Chapultepec | Statement: [San Lázaro metro station, openedWithSection, Line 1 section Zaragoza–Chapultepec]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openedWithSection Context triple: [San Lázaro metro station, openedWithSection, Line 1 section Zaragoza–Chapultepec]
-
A.
openedInSections
Indicates that something has been opened or made accessible in multiple distinct sections or parts.
-
B.
openedSectionBetween
Indicates that one entity has created or established an open section, gap, or interval between itself and another entity.
-
C.
openedWith
Indicates that an entity is opened, initiated, or accessed using a specified tool, method, or instrument.
-
D.
openedAs
Indicates that one entity began operating, functioning, or being available to the public under the form, name, or role of another entity.
-
E.
openedIn
Indicates that an entity (such as a business, event, or institution) began operating or was inaugurated in a specific time period or location.
- 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_69c68811dd1c8190ac460bb39e64e1f0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea552a688190a00f5d0ad982f787 |
completed | March 27, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69c6e7644648819096a5e2de5d0dbe97 |
completed | March 27, 2026, 8:24 p.m. |
| PDg | Predicate description generation | batch_69c6ea539f5c81908001524149903559 |
completed | March 27, 2026, 8:36 p.m. |
Created at: March 27, 2026, 2:55 p.m.