Triple
T30158861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British coastal time signal network |
E766600
|
entity |
| Predicate | typicalSignalEvent |
P7008
|
FINISHED |
| Object | daily time drop of a time ball |
—
|
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: daily time drop of a time ball | Statement: [British coastal time signal network, typicalSignalEvent, daily time drop of a time ball]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSignalEvent Context triple: [British coastal time signal network, typicalSignalEvent, daily time drop of a time ball]
-
A.
typicalEvent
chosen
Indicates that the associated event is a common, characteristic, or prototypical occurrence for the given entity or situation.
-
B.
signalType
Indicates the specific kind or category of signal associated with or used by an entity or interaction.
-
C.
symbolicEvent
Indicates that an event functions primarily as a symbol or representation of something else, such as an idea, concept, or broader situation.
-
D.
peakEvent
Indicates the occurrence of a maximum or most intense point within a process, activity, or measurable phenomenon.
-
E.
typicalTrigger
Indicates that one entity commonly or characteristically causes, initiates, or brings about the occurrence of another entity or event.
- 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_69f22479cd088190ab4c6f3fce39d1c5 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e0f3d88190a4ee7b0673f1ef90 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 7:21 p.m.