Triple
T6131855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lone Star Park |
E136736
|
entity |
| Predicate | hasTotalCapacity |
P13466
|
FINISHED |
| Object | approximately 50000 |
—
|
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: approximately 50000 | Statement: [Lone Star Park, hasTotalCapacity, approximately 50000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTotalCapacity Context triple: [Lone Star Park, hasTotalCapacity, approximately 50000]
-
A.
totalCapacity
chosen
Indicates the maximum amount or volume that something can hold or accommodate in total.
-
B.
hasCapacityTo
Indicates that one entity possesses the ability, power, or potential to perform an action or bring about a particular effect in relation to another entity or context.
-
C.
hasCapacityProperty
Indicates that an entity is associated with a capacity-related characteristic, such as volume, throughput, or maximum amount it can hold or handle.
-
D.
hasCapacityType
Indicates that an entity possesses a specific kind or classification of capacity or capability.
-
E.
maximumCapacity
Indicates the greatest allowable or designed amount of something that an entity can hold, contain, or handle.
- 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_69c008a0a37c81908e5b4f879158afb3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05c4f7ad8819096b09ddd312453fb |
completed | March 22, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69c055f19b0c81908be34a00ab218723 |
completed | March 22, 2026, 8:49 p.m. |
Created at: March 22, 2026, 4:15 p.m.