Triple
T2073829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barrowland Ballroom |
E44875
|
entity |
| Predicate | hasStandingArea |
P34773
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Barrowland Ballroom, hasStandingArea, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStandingArea Context triple: [Barrowland Ballroom, hasStandingArea, yes]
-
A.
hasSafeStandingAreas
Indicates that designated locations within an area provide secure, stable, and protected spots where individuals can safely stand.
-
B.
hasPedestrianArea
Indicates that a location or zone includes a designated area intended for pedestrian use only or primarily.
-
C.
hasTerrace
Indicates that one entity includes, features, or is equipped with a terrace as part of its structure or property.
-
D.
hasRooftopSpace
Indicates that an entity includes or provides an accessible rooftop area intended for use or occupancy.
-
E.
hasParkArea
Indicates that an entity includes or is associated with a designated park or recreational area within its boundaries.
- 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_69a88916c2b48190a5ca2e9b12cad3ed |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abba101c008190840763d2f28fa8d7 |
completed | March 7, 2026, 5:39 a.m. |
| PD | Predicate disambiguation | batch_69abb7b0edac8190a58eabee55f73deb |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb85fe7a08190b991b1f23bc34f93 |
completed | March 7, 2026, 5:32 a.m. |
Created at: March 4, 2026, 7:41 p.m.