Triple
T37001188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlton Campus emergency department |
E915353
|
entity |
| Predicate | openAllDays |
P186892
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Charlton Campus emergency department, openAllDays, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openAllDays Context triple: [Charlton Campus emergency department, openAllDays, true]
-
A.
isOpenAllYear
Indicates that the subject remains available or operational throughout the entire year without seasonal closures.
-
B.
openingDay
Indicates the specific day on which something, typically an event, season, or venue, officially begins or first opens to the public.
-
C.
openingTime
Indicates the time at which a place, service, or event begins operating or becomes accessible.
-
D.
operatesAllTimes
Indicates that the action, service, or process is continuously in operation at all times without interruption.
-
E.
openedBetween
Indicates that an entity was opened during a time interval that falls between two specified temporal bounds.
- 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_69f76e8f1a8c81909db172ed31304971 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb154c0fe08190a2e41e7a29b6055f |
completed | May 6, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69f9fecc005c8190be082a8689193745 |
completed | May 5, 2026, 2:29 p.m. |
| PDg | Predicate description generation | batch_69fb154b5f8c819089103b41f51a1639 |
completed | May 6, 2026, 10:17 a.m. |
Created at: May 3, 2026, 4:14 p.m.