Triple
T183776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pizza Hut Park |
E3934
|
entity |
| Predicate | hasFieldType |
P4541
|
FINISHED |
| Object | rectangular pitch |
—
|
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: rectangular pitch | Statement: [Pizza Hut Park, hasFieldType, rectangular pitch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFieldType Context triple: [Pizza Hut Park, hasFieldType, rectangular pitch]
-
A.
hasPropertyType
Indicates that an entity possesses or is associated with a specific type or category of property.
-
B.
fieldType
chosen
Indicates the classification or category that defines the nature or kind of a given field within a structure or context.
-
C.
hasModelType
Indicates that an entity is associated with or classified under a specific model type.
-
D.
hasTypeName
Indicates that an entity is associated with a specific type name used to classify or identify its kind.
-
E.
hasRecordType
Indicates that an entity is associated with or classified under a specific type or category of record.
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25926be9c8190a4cfce66f57589d1 |
completed | Feb. 28, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69a2566dfc388190988b1b42d5daaafe |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.