Triple
T96721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanglewood |
E1947
|
entity |
| Predicate | hasCapacityType |
P4139
|
FINISHED |
| Object | covered seating and lawn seating |
—
|
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: covered seating and lawn seating | Statement: [Tanglewood, hasCapacityType, covered seating and lawn seating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCapacityType Context triple: [Tanglewood, hasCapacityType, covered seating and lawn seating]
-
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.
canHold
Indicates that one entity has the capacity or ability to contain, support, or carry another entity.
-
C.
hasMaterialType
Indicates that something is composed of, made from, or characterized by a specific type of material.
-
D.
hasCollectionType
Indicates that an entity is associated with or organized under a specific type or category of collection.
-
E.
hasInfrastructureType
Indicates that an entity possesses or is associated with a specific category or type of infrastructure.
- 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a250cb400c8190b56343bbe19b48c7 |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ebd19c48190bab291fea0ecc0c2 |
completed | Feb. 28, 2026, 2:11 a.m. |
| PDg | Predicate description generation | batch_69a250ca7eec8190b31f7e61f5e3ee1f |
completed | Feb. 28, 2026, 2:19 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.