Triple
T2632014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Los Héroes |
E59655
|
entity |
| Predicate | line1SectionOpenedWith |
P37968
|
FINISHED |
| Object | San Pablo–La Moneda section |
—
|
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: San Pablo–La Moneda section | Statement: [Los Héroes, line1SectionOpenedWith, San Pablo–La Moneda section]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: line1SectionOpenedWith Context triple: [Los Héroes, line1SectionOpenedWith, San Pablo–La Moneda section]
-
A.
originalLineOpened
chosen
Indicates that a transportation or service line began its initial operation or was first opened for use.
-
B.
openedSectionBetween
Indicates that one entity has created or established an open section, gap, or interval between itself and another entity.
-
C.
firstLineOpened
Indicates that the first line of something (e.g., a document, file, or text block) has been opened or accessed.
-
D.
openedFirstLine
Indicates that one entity initiated the opening of something (e.g., a file, document, or interface) before any other entity did, being the first to perform the opening action.
-
E.
firstSectionOpened
Indicates that the initial section in a sequence or structure has been opened or activated.
- 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_69ab4ac8596c8190b34997e73d9e991c |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abdb0e7b888190bfa5d2e33f00ec0f |
completed | March 7, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69abd810d7f481908e81c305772c4c14 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.