Triple
T11288924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plaza Mayor of Astorga |
E267270
|
entity |
| Predicate | hasClockFigures |
P98315
|
FINISHED |
| Object | mechanical figures that strike the hours |
—
|
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: mechanical figures that strike the hours | Statement: [Plaza Mayor of Astorga, hasClockFigures, mechanical figures that strike the hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClockFigures Context triple: [Plaza Mayor of Astorga, hasClockFigures, mechanical figures that strike the hours]
-
A.
hasClockFaces
Indicates that an object is equipped with one or more clock faces.
-
B.
hasClock
Indicates that one entity possesses, contains, or is equipped with a clock.
-
C.
clockShows
Indicates that a clock displays or presents a particular time or temporal value.
-
D.
clockType
Indicates the type or category of a clock associated with an entity (e.g., analog, digital, system clock, etc.).
-
E.
chronometerNumber
Indicates that an entity has been assigned a specific chronometer identification number, linking it to that unique timekeeping device record.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e98875a08190b8509fe55e49d52d |
completed | April 9, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69d787a240588190aa097298f951c915 |
completed | April 9, 2026, 11:04 a.m. |
| PDg | Predicate description generation | batch_69d796d049e88190a9fd7508f477f541 |
completed | April 9, 2026, 12:08 p.m. |
Created at: April 8, 2026, 9:32 p.m.