Triple
T36924599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. John’s Parish House |
E913302
|
entity |
| Predicate | hasMeetingSpaces |
P15338
|
FINISHED |
| Object | parish meeting rooms |
—
|
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: parish meeting rooms | Statement: [St. John’s Parish House, hasMeetingSpaces, parish meeting rooms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeetingSpaces Context triple: [St. John’s Parish House, hasMeetingSpaces, parish meeting rooms]
-
A.
hasConferenceSpace
chosen
Indicates that an entity provides or includes dedicated space suitable for holding conferences, meetings, or similar gatherings.
-
B.
hasMeetingLocation
Indicates that an entity (such as a meeting or event) takes place at or is associated with a specific location.
-
C.
hasOpenSpaces
Indicates that an entity possesses or includes areas that are unobstructed, unoccupied, or otherwise open.
-
D.
hasMeetings
Indicates that an entity participates in or is associated with one or more scheduled meetings.
-
E.
hasRoom
Indicates that an entity possesses, contains, or is associated with a specific room.
- 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_69f76e885b848190bad82c87e9525486 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff76ac40988190a34d858b5472ee2b |
completed | May 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69ff760a90948190a12fcb80e6e3e14b |
completed | May 9, 2026, 5:59 p.m. |
Created at: May 3, 2026, 4:13 p.m.