Triple
T29102559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tolka Park |
E736674
|
entity |
| Predicate | safetyCapacity |
P170678
|
FINISHED |
| Object | reduced from historic higher capacities |
—
|
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: reduced from historic higher capacities | Statement: [Tolka Park, safetyCapacity, reduced from historic higher capacities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyCapacity Context triple: [Tolka Park, safetyCapacity, reduced from historic higher capacities]
-
A.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
-
B.
unitCapacity
Indicates the maximum quantity or load that a single unit is designed or allowed to hold, process, or accommodate.
-
C.
standingCapacity
Indicates the maximum number of people that are allowed or able to stand in a given space or vehicle.
-
D.
launcherCapacity
Indicates the maximum number or size of items that a launcher is designed to hold or deploy.
-
E.
sleepingCapacity
Indicates the maximum number of people or occupants that can sleep in or be accommodated for sleeping by something.
- 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_69f077ec765c81909474c88bcc8bab43 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f693ffa7908190aa4c451b16df9be6 |
completed | May 3, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69f690eb1e948190aab41a89969519a5 |
completed | May 3, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69f6938244648190a553b532387b812c |
completed | May 3, 2026, 12:14 a.m. |
Created at: April 28, 2026, 11:13 a.m.