Triple
T18963738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Worthing railway station |
E463975
|
entity |
| Predicate | hasLoudspeakers |
P70173
|
FINISHED |
| Object | public address system |
—
|
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: public address system | Statement: [East Worthing railway station, hasLoudspeakers, public address system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLoudspeakers Context triple: [East Worthing railway station, hasLoudspeakers, public address system]
-
A.
hasSoundSystem
chosen
Indicates that an entity is equipped with or includes a sound system as one of its features.
-
B.
hasSpeakerType
Indicates that an entity functions in a particular role or category as a speaker (e.g., narrator, character, announcer) within a given context.
-
C.
hasNumberOfSpeakersCategory
Indicates a classification of an entity based on the number of speakers associated with it, typically grouping it into predefined size categories.
-
D.
hasLFEChannels
Indicates that an entity includes or is associated with one or more Low-Frequency Effects (LFE) audio channels.
-
E.
numberOfSpeakersStatus
Indicates the status or condition of information about how many speakers are involved (e.g., whether the number of speakers is known, estimated, missing, or otherwise qualified).
- 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_69d8dcffc278819086792a4ebfddfafa |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d5d420f481909aa22a0d22ac4af1 |
completed | April 20, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69e4a2f437648190b85650dae8885d48 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, noon