Triple
T31012331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madrid–Barcelona high-speed line |
E790239
|
entity |
| Predicate | fullOpeningSection |
P170907
|
FINISHED |
| Object | Madrid–Barcelona section |
—
|
NE NERFINISHED |
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: Madrid–Barcelona section | Statement: [Madrid–Barcelona high-speed line, fullOpeningSection, Madrid–Barcelona section]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fullOpeningSection Context triple: [Madrid–Barcelona high-speed line, fullOpeningSection, Madrid–Barcelona section]
-
A.
originalOpeningSection
Indicates that one section is the initial or first opening section of another work, document, or structured content.
-
B.
firstSectionOpened
Indicates that the initial section in a sequence or structure has been opened or activated.
-
C.
openingTheme
Indicates that one entity serves as the opening theme (such as a song or musical piece) for another entity, typically a show, series, or similar work.
-
D.
openingPractice
Indicates the practice or rehearsal of opening moves, procedures, or initial actions in a given context.
-
E.
openedSectionBetween
Indicates that one entity has created or established an open section, gap, or interval between itself and another entity.
- 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_69f224c73ca48190a1e46cb58ad4045b |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f695f9fe7c819084322bf6cdc70a13 |
completed | May 3, 2026, 12:25 a.m. |
| PD | Predicate disambiguation | batch_69f690ef92308190903a54fc74233269 |
completed | May 3, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69f695385a2881908cc28ef97fffc867 |
completed | May 3, 2026, 12:22 a.m. |
Created at: April 29, 2026, 8:57 p.m.